Merge version_1 into main #1
384
src/app/page.tsx
384
src/app/page.tsx
@@ -11,7 +11,7 @@ import MetricCardOne from '@/components/sections/metrics/MetricCardOne';
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import NavbarLayoutFloatingOverlay from '@/components/navbar/NavbarLayoutFloatingOverlay/NavbarLayoutFloatingOverlay';
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import SocialProofOne from '@/components/sections/socialProof/SocialProofOne';
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import TextAbout from '@/components/sections/about/TextAbout';
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import { CheckCircle, Target, TrendingUp } from "lucide-react";
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import { CheckCircle, Target, TrendingUp, Zap, BrainCircuit, Shield, Database } from "lucide-react";
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export default function LandingPage() {
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return (
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@@ -28,282 +28,128 @@ export default function LandingPage() {
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headingFontWeight="medium"
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>
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<ReactLenis root>
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<div id="nav" data-section="nav">
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<NavbarLayoutFloatingOverlay
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navItems={[
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{
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name: "Features",
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id: "#features",
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},
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{
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name: "Performance",
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id: "#metrics",
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},
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{
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name: "Explainability",
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id: "#algorithm",
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},
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{
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name: "Contact",
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id: "#contact",
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},
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]}
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brandName="DiaPredict"
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/>
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</div>
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<div id="nav" data-section="nav">
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<NavbarLayoutFloatingOverlay
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navItems={[
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{ name: "Features", id: "features" },
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{ name: "Performance", id: "metrics" },
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{ name: "Explainability", id: "algorithm" },
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{ name: "Contact", id: "contact" },
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]}
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brandName="DiaPredict"
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/>
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</div>
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<div id="hero" data-section="hero">
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<HeroSplit
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background={{
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variant: "gradient-bars",
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}}
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title="Clinically Actionable Early Diabetes Detection"
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description="Revolutionizing patient outcomes with production-grade ML engines. Precise, explainable, and built for modern healthcare."
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buttons={[
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{
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text: "Deploy Pipeline",
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href: "#contact",
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},
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]}
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imageSrc="http://img.b2bpic.net/free-photo/professional-medic-giving-vitamins-medical-drugs-female-patient_482257-100693.jpg"
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mediaAnimation="slide-up"
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avatars={[
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{
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src: "http://img.b2bpic.net/free-photo/medic-expert-uses-thermometer-find-right-diagnostic-symptoms_482257-122834.jpg",
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alt: "Doctor profile 1",
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},
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{
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src: "http://img.b2bpic.net/free-photo/student-doing-academic-research-internet-gain-career-knowledge_482257-124934.jpg",
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alt: "Doctor profile 2",
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},
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{
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src: "http://img.b2bpic.net/free-photo/medical-professionals-meeting-examining-organs-ct-scan-results_482257-123078.jpg",
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alt: "Doctor profile 3",
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},
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{
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src: "http://img.b2bpic.net/free-photo/medical-expert-patient-meeting-check-up-appointment_482257-108187.jpg",
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alt: "Doctor profile 4",
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},
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{
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src: "http://img.b2bpic.net/free-photo/african-american-physician-gives-professional-advice-woman-patient_482257-107489.jpg",
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alt: "Doctor profile 5",
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},
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]}
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avatarText="Trusted by 500+ clinical practitioners"
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marqueeItems={[
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{
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type: "text",
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text: "High Accuracy",
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},
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{
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type: "text",
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text: "SHAP Interpretable",
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},
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{
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type: "text",
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text: "FDA Compliant Logic",
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},
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{
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type: "text",
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text: "Fast Deployment",
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},
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{
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type: "text",
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text: "Scalable Infrastructure",
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},
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]}
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/>
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</div>
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<div id="hero" data-section="hero">
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<HeroSplit
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background={{ variant: "gradient-bars" }}
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title="Clinically Actionable Early Diabetes Detection"
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description="Revolutionizing patient outcomes with production-grade ML engines. Precise, explainable, and built for modern healthcare."
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buttons={[{ text: "Deploy Pipeline", href: "#contact" }]}
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imageSrc="http://img.b2bpic.net/free-photo/professional-medic-giving-vitamins-medical-drugs-female-patient_482257-100693.jpg"
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mediaAnimation="slide-up"
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avatars={[
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{ src: "http://img.b2bpic.net/free-photo/medic-expert-uses-thermometer-find-right-diagnostic-symptoms_482257-122834.jpg", alt: "Doctor profile 1" },
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{ src: "http://img.b2bpic.net/free-photo/student-doing-academic-research-internet-gain-career-knowledge_482257-124934.jpg", alt: "Doctor profile 2" },
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{ src: "http://img.b2bpic.net/free-photo/medical-professionals-meeting-examining-organs-ct-scan-results_482257-123078.jpg", alt: "Doctor profile 3" },
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{ src: "http://img.b2bpic.net/free-photo/medical-expert-patient-meeting-check-up-appointment_482257-108187.jpg", alt: "Doctor profile 4" },
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{ src: "http://img.b2bpic.net/free-photo/african-american-physician-gives-professional-advice-woman-patient_482257-107489.jpg", alt: "Doctor profile 5" }
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]}
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avatarText="Trusted by 500+ clinical practitioners"
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marqueeItems={[
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{ type: "text", text: "High Accuracy" },
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{ type: "text", text: "SHAP Interpretable" },
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{ type: "text", text: "FDA Compliant Logic" },
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{ type: "text", text: "Fast Deployment" },
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{ type: "text", text: "Scalable Infrastructure" }
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]}
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/>
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</div>
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<div id="about" data-section="about">
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<TextAbout
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useInvertedBackground={true}
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title="Machine Learning Meets Clinical Reality"
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buttons={[
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{
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text: "Learn About Our Engine",
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href: "#features",
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},
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]}
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/>
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</div>
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<div id="about" data-section="about">
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<TextAbout
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useInvertedBackground={true}
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title="Machine Learning Meets Clinical Reality"
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buttons={[{ text: "Learn About Our Engine", href: "#features" }]}
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/>
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</div>
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<div id="features" data-section="features">
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<FeatureCardTwentySix
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textboxLayout="default"
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useInvertedBackground={false}
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features={[
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{
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title: "Logical Imputation",
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description: "Stratified median imputation ensuring data integrity for missing clinical markers.",
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buttonIcon: "Zap",
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imageSrc: "http://img.b2bpic.net/free-photo/beautiful-optical-fiber-detail_23-2149182559.jpg",
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},
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{
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title: "Feature Engineering",
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description: "Creation of metabolic indices to maximize predictive clarity of patient profiles.",
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buttonIcon: "BrainCircuit",
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imageSrc: "http://img.b2bpic.net/free-photo/healthcare-professionals-review-mri-scan-test-results-neurology-x-rays_482257-123104.jpg",
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},
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{
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title: "SMOTE Balancing",
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description: "Ensuring the minority diabetic class is represented for robust generalization.",
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buttonIcon: "Shield",
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imageSrc: "http://img.b2bpic.net/free-photo/engineer-data-center-fixing-issues_482257-90996.jpg",
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},
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{
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title: "Clinical Scalability",
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description: "Standardized scaling for optimal convergence across SVM and Ensemble models.",
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buttonIcon: "Database",
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imageSrc: "http://img.b2bpic.net/free-photo/doctor-man-analyze-cells-laptop_482257-119853.jpg",
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},
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]}
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title="High-Performance Data Architecture"
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description="Built for rigorous healthcare demands, our pipeline ensures maximum predictive power."
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/>
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</div>
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<div id="features" data-section="features">
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<FeatureCardTwentySix
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textboxLayout="default"
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useInvertedBackground={false}
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features={[
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{ title: "Logical Imputation", description: "Stratified median imputation ensuring data integrity for missing clinical markers.", buttonIcon: Zap, imageSrc: "http://img.b2bpic.net/free-photo/beautiful-optical-fiber-detail_23-2149182559.jpg" },
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{ title: "Feature Engineering", description: "Creation of metabolic indices to maximize predictive clarity of patient profiles.", buttonIcon: BrainCircuit, imageSrc: "http://img.b2bpic.net/free-photo/healthcare-professionals-review-mri-scan-test-results-neurology-x-rays_482257-123104.jpg" },
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{ title: "SMOTE Balancing", description: "Ensuring the minority diabetic class is represented for robust generalization.", buttonIcon: Shield, imageSrc: "http://img.b2bpic.net/free-photo/engineer-data-center-fixing-issues_482257-90996.jpg" },
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{ title: "Clinical Scalability", description: "Standardized scaling for optimal convergence across SVM and Ensemble models.", buttonIcon: Database, imageSrc: "http://img.b2bpic.net/free-photo/doctor-man-analyze-cells-laptop_482257-119853.jpg" }
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]}
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title="High-Performance Data Architecture"
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description="Built for rigorous healthcare demands, our pipeline ensures maximum predictive power."
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/>
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</div>
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<div id="metrics" data-section="metrics">
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<MetricCardOne
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textboxLayout="default"
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gridVariant="bento-grid"
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useInvertedBackground={true}
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metrics={[
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{
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id: "1",
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value: "98.5%",
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title: "AUC-ROC",
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description: "Model discrimination capability.",
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icon: TrendingUp,
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},
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{
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id: "2",
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value: "F1-Score",
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title: "Optimized",
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description: "Prioritizing False Negative reduction.",
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icon: Target,
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},
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{
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id: "3",
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value: "10-Fold",
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title: "Validation",
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description: "Rigorous cross-validation training.",
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icon: CheckCircle,
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},
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]}
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title="Proven Performance Rigor"
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description="Validation metrics designed to minimize False Negatives in clinical settings."
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/>
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</div>
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<div id="metrics" data-section="metrics">
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<MetricCardOne
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textboxLayout="default"
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gridVariant="bento-grid"
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animationType="slide-up"
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useInvertedBackground={true}
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metrics={[
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{ id: "1", value: "98.5%", title: "AUC-ROC", description: "Model discrimination capability.", icon: TrendingUp },
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{ id: "2", value: "F1-Score", title: "Optimized", description: "Prioritizing False Negative reduction.", icon: Target },
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{ id: "3", value: "10-Fold", title: "Validation", description: "Rigorous cross-validation training.", icon: CheckCircle }
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]}
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title="Proven Performance Rigor"
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description="Validation metrics designed to minimize False Negatives in clinical settings."
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/>
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</div>
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<div id="algorithm" data-section="algorithm">
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<FaqSplitText
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useInvertedBackground={false}
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faqs={[
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{
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id: "1",
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title: "How is the model explained?",
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content: "We use SHAP integration to output the exact contribution of each patient feature to the final risk score.",
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},
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{
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id: "2",
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title: "Which models are deployed?",
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content: "Logistic Regression, Decision Trees, Random Forest (with GridSearchCV), and RBF-Kernel SVMs.",
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},
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{
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id: "3",
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title: "Is it clinical ready?",
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content: "Yes, with F1-Score optimization and strict False Negative minimization protocols.",
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},
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]}
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sideTitle="Explainable Predictive Engine"
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sideDescription="Why does the model predict high risk? SHAP integration provides the 'Why' for every doctor."
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faqsAnimation="slide-up"
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/>
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</div>
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<div id="algorithm" data-section="algorithm">
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<FaqSplitText
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useInvertedBackground={false}
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faqs={[
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{ id: "1", title: "How is the model explained?", content: "We use SHAP integration to output the exact contribution of each patient feature to the final risk score." },
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{ id: "2", title: "Which models are deployed?", content: "Logistic Regression, Decision Trees, Random Forest (with GridSearchCV), and RBF-Kernel SVMs." },
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{ id: "3", title: "Is it clinical ready?", content: "Yes, with F1-Score optimization and strict False Negative minimization protocols." }
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]}
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sideTitle="Explainable Predictive Engine"
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sideDescription="Why does the model predict high risk? SHAP integration provides the 'Why' for every doctor."
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faqsAnimation="slide-up"
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/>
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</div>
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<div id="social" data-section="social">
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<SocialProofOne
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textboxLayout="default"
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useInvertedBackground={true}
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names={[
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"HealthCare System",
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"Medical Research Lab",
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"Clinical Diagnostic Corp",
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"Biotech Systems",
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"Wellness Analytics",
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"Digital Health Partners",
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"Patient Care Analytics",
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]}
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title="Trusted by Healthcare Innovators"
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description="We partner with leading organizations to advance diagnostic precision."
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/>
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</div>
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<div id="social" data-section="social">
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<SocialProofOne
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textboxLayout="default"
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useInvertedBackground={true}
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names={["HealthCare System", "Medical Research Lab", "Clinical Diagnostic Corp", "Biotech Systems", "Wellness Analytics", "Digital Health Partners", "Patient Care Analytics"]}
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title="Trusted by Healthcare Innovators"
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description="We partner with leading organizations to advance diagnostic precision."
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/>
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</div>
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<div id="contact" data-section="contact">
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<ContactCTA
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useInvertedBackground={false}
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background={{
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variant: "sparkles-gradient",
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}}
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tag="Get Started"
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title="Ready to Deploy the Engine?"
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description="Join the future of diagnostic health-tech."
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buttons={[
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{
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text: "Contact Our Engineering Team",
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href: "#",
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},
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]}
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/>
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</div>
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<div id="contact" data-section="contact">
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<ContactCTA
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useInvertedBackground={false}
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background={{ variant: "sparkles-gradient" }}
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tag="Get Started"
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title="Ready to Deploy the Engine?"
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description="Join the future of diagnostic health-tech."
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buttons={[{ text: "Contact Our Engineering Team", href: "#" }]}
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||||
/>
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</div>
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||||
<div id="footer" data-section="footer">
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||||
<FooterBaseCard
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||||
logoText="DiaPredict Engine"
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||||
columns={[
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||||
{
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||||
title: "Platform",
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||||
items: [
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||||
{
|
||||
label: "Models",
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||||
href: "#",
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||||
},
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||||
{
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||||
label: "Metrics",
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||||
href: "#",
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||||
},
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||||
],
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||||
},
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||||
{
|
||||
title: "Explainability",
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||||
items: [
|
||||
{
|
||||
label: "SHAP Integration",
|
||||
href: "#",
|
||||
},
|
||||
{
|
||||
label: "Documentation",
|
||||
href: "#",
|
||||
},
|
||||
],
|
||||
},
|
||||
{
|
||||
title: "Company",
|
||||
items: [
|
||||
{
|
||||
label: "About",
|
||||
href: "#",
|
||||
},
|
||||
{
|
||||
label: "Privacy",
|
||||
href: "#",
|
||||
},
|
||||
],
|
||||
},
|
||||
]}
|
||||
/>
|
||||
</div>
|
||||
<div id="footer" data-section="footer">
|
||||
<FooterBaseCard
|
||||
logoText="DiaPredict Engine"
|
||||
columns={[
|
||||
{ title: "Platform", items: [{ label: "Models", href: "#" }, { label: "Metrics", href: "#" }] },
|
||||
{ title: "Explainability", items: [{ label: "SHAP Integration", href: "#" }, { label: "Documentation", href: "#" }] },
|
||||
{ title: "Company", items: [{ label: "About", href: "#" }, { label: "Privacy", href: "#" }] }
|
||||
]}
|
||||
/>
|
||||
</div>
|
||||
</ReactLenis>
|
||||
</ThemeProvider>
|
||||
);
|
||||
|
||||
Reference in New Issue
Block a user