Merge version_1 into main #1

Merged
bender merged 1 commits from version_1 into main 2026-04-24 18:05:01 +00:00

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@@ -11,7 +11,7 @@ import MetricCardOne from '@/components/sections/metrics/MetricCardOne';
import NavbarLayoutFloatingOverlay from '@/components/navbar/NavbarLayoutFloatingOverlay/NavbarLayoutFloatingOverlay';
import SocialProofOne from '@/components/sections/socialProof/SocialProofOne';
import TextAbout from '@/components/sections/about/TextAbout';
import { CheckCircle, Target, TrendingUp } from "lucide-react";
import { CheckCircle, Target, TrendingUp, Zap, BrainCircuit, Shield, Database } from "lucide-react";
export default function LandingPage() {
return (
@@ -28,282 +28,128 @@ export default function LandingPage() {
headingFontWeight="medium"
>
<ReactLenis root>
<div id="nav" data-section="nav">
<NavbarLayoutFloatingOverlay
navItems={[
{
name: "Features",
id: "#features",
},
{
name: "Performance",
id: "#metrics",
},
{
name: "Explainability",
id: "#algorithm",
},
{
name: "Contact",
id: "#contact",
},
]}
brandName="DiaPredict"
/>
</div>
<div id="nav" data-section="nav">
<NavbarLayoutFloatingOverlay
navItems={[
{ name: "Features", id: "features" },
{ name: "Performance", id: "metrics" },
{ name: "Explainability", id: "algorithm" },
{ name: "Contact", id: "contact" },
]}
brandName="DiaPredict"
/>
</div>
<div id="hero" data-section="hero">
<HeroSplit
background={{
variant: "gradient-bars",
}}
title="Clinically Actionable Early Diabetes Detection"
description="Revolutionizing patient outcomes with production-grade ML engines. Precise, explainable, and built for modern healthcare."
buttons={[
{
text: "Deploy Pipeline",
href: "#contact",
},
]}
imageSrc="http://img.b2bpic.net/free-photo/professional-medic-giving-vitamins-medical-drugs-female-patient_482257-100693.jpg"
mediaAnimation="slide-up"
avatars={[
{
src: "http://img.b2bpic.net/free-photo/medic-expert-uses-thermometer-find-right-diagnostic-symptoms_482257-122834.jpg",
alt: "Doctor profile 1",
},
{
src: "http://img.b2bpic.net/free-photo/student-doing-academic-research-internet-gain-career-knowledge_482257-124934.jpg",
alt: "Doctor profile 2",
},
{
src: "http://img.b2bpic.net/free-photo/medical-professionals-meeting-examining-organs-ct-scan-results_482257-123078.jpg",
alt: "Doctor profile 3",
},
{
src: "http://img.b2bpic.net/free-photo/medical-expert-patient-meeting-check-up-appointment_482257-108187.jpg",
alt: "Doctor profile 4",
},
{
src: "http://img.b2bpic.net/free-photo/african-american-physician-gives-professional-advice-woman-patient_482257-107489.jpg",
alt: "Doctor profile 5",
},
]}
avatarText="Trusted by 500+ clinical practitioners"
marqueeItems={[
{
type: "text",
text: "High Accuracy",
},
{
type: "text",
text: "SHAP Interpretable",
},
{
type: "text",
text: "FDA Compliant Logic",
},
{
type: "text",
text: "Fast Deployment",
},
{
type: "text",
text: "Scalable Infrastructure",
},
]}
/>
</div>
<div id="hero" data-section="hero">
<HeroSplit
background={{ variant: "gradient-bars" }}
title="Clinically Actionable Early Diabetes Detection"
description="Revolutionizing patient outcomes with production-grade ML engines. Precise, explainable, and built for modern healthcare."
buttons={[{ text: "Deploy Pipeline", href: "#contact" }]}
imageSrc="http://img.b2bpic.net/free-photo/professional-medic-giving-vitamins-medical-drugs-female-patient_482257-100693.jpg"
mediaAnimation="slide-up"
avatars={[
{ src: "http://img.b2bpic.net/free-photo/medic-expert-uses-thermometer-find-right-diagnostic-symptoms_482257-122834.jpg", alt: "Doctor profile 1" },
{ src: "http://img.b2bpic.net/free-photo/student-doing-academic-research-internet-gain-career-knowledge_482257-124934.jpg", alt: "Doctor profile 2" },
{ src: "http://img.b2bpic.net/free-photo/medical-professionals-meeting-examining-organs-ct-scan-results_482257-123078.jpg", alt: "Doctor profile 3" },
{ src: "http://img.b2bpic.net/free-photo/medical-expert-patient-meeting-check-up-appointment_482257-108187.jpg", alt: "Doctor profile 4" },
{ src: "http://img.b2bpic.net/free-photo/african-american-physician-gives-professional-advice-woman-patient_482257-107489.jpg", alt: "Doctor profile 5" }
]}
avatarText="Trusted by 500+ clinical practitioners"
marqueeItems={[
{ type: "text", text: "High Accuracy" },
{ type: "text", text: "SHAP Interpretable" },
{ type: "text", text: "FDA Compliant Logic" },
{ type: "text", text: "Fast Deployment" },
{ type: "text", text: "Scalable Infrastructure" }
]}
/>
</div>
<div id="about" data-section="about">
<TextAbout
useInvertedBackground={true}
title="Machine Learning Meets Clinical Reality"
buttons={[
{
text: "Learn About Our Engine",
href: "#features",
},
]}
/>
</div>
<div id="about" data-section="about">
<TextAbout
useInvertedBackground={true}
title="Machine Learning Meets Clinical Reality"
buttons={[{ text: "Learn About Our Engine", href: "#features" }]}
/>
</div>
<div id="features" data-section="features">
<FeatureCardTwentySix
textboxLayout="default"
useInvertedBackground={false}
features={[
{
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",
},
{
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",
},
{
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",
},
{
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",
},
]}
title="High-Performance Data Architecture"
description="Built for rigorous healthcare demands, our pipeline ensures maximum predictive power."
/>
</div>
<div id="features" data-section="features">
<FeatureCardTwentySix
textboxLayout="default"
useInvertedBackground={false}
features={[
{ 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" },
{ 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" },
{ 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" },
{ 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" }
]}
title="High-Performance Data Architecture"
description="Built for rigorous healthcare demands, our pipeline ensures maximum predictive power."
/>
</div>
<div id="metrics" data-section="metrics">
<MetricCardOne
textboxLayout="default"
gridVariant="bento-grid"
useInvertedBackground={true}
metrics={[
{
id: "1",
value: "98.5%",
title: "AUC-ROC",
description: "Model discrimination capability.",
icon: TrendingUp,
},
{
id: "2",
value: "F1-Score",
title: "Optimized",
description: "Prioritizing False Negative reduction.",
icon: Target,
},
{
id: "3",
value: "10-Fold",
title: "Validation",
description: "Rigorous cross-validation training.",
icon: CheckCircle,
},
]}
title="Proven Performance Rigor"
description="Validation metrics designed to minimize False Negatives in clinical settings."
/>
</div>
<div id="metrics" data-section="metrics">
<MetricCardOne
textboxLayout="default"
gridVariant="bento-grid"
animationType="slide-up"
useInvertedBackground={true}
metrics={[
{ id: "1", value: "98.5%", title: "AUC-ROC", description: "Model discrimination capability.", icon: TrendingUp },
{ id: "2", value: "F1-Score", title: "Optimized", description: "Prioritizing False Negative reduction.", icon: Target },
{ id: "3", value: "10-Fold", title: "Validation", description: "Rigorous cross-validation training.", icon: CheckCircle }
]}
title="Proven Performance Rigor"
description="Validation metrics designed to minimize False Negatives in clinical settings."
/>
</div>
<div id="algorithm" data-section="algorithm">
<FaqSplitText
useInvertedBackground={false}
faqs={[
{
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.",
},
{
id: "2",
title: "Which models are deployed?",
content: "Logistic Regression, Decision Trees, Random Forest (with GridSearchCV), and RBF-Kernel SVMs.",
},
{
id: "3",
title: "Is it clinical ready?",
content: "Yes, with F1-Score optimization and strict False Negative minimization protocols.",
},
]}
sideTitle="Explainable Predictive Engine"
sideDescription="Why does the model predict high risk? SHAP integration provides the 'Why' for every doctor."
faqsAnimation="slide-up"
/>
</div>
<div id="algorithm" data-section="algorithm">
<FaqSplitText
useInvertedBackground={false}
faqs={[
{ 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." },
{ id: "2", title: "Which models are deployed?", content: "Logistic Regression, Decision Trees, Random Forest (with GridSearchCV), and RBF-Kernel SVMs." },
{ id: "3", title: "Is it clinical ready?", content: "Yes, with F1-Score optimization and strict False Negative minimization protocols." }
]}
sideTitle="Explainable Predictive Engine"
sideDescription="Why does the model predict high risk? SHAP integration provides the 'Why' for every doctor."
faqsAnimation="slide-up"
/>
</div>
<div id="social" data-section="social">
<SocialProofOne
textboxLayout="default"
useInvertedBackground={true}
names={[
"HealthCare System",
"Medical Research Lab",
"Clinical Diagnostic Corp",
"Biotech Systems",
"Wellness Analytics",
"Digital Health Partners",
"Patient Care Analytics",
]}
title="Trusted by Healthcare Innovators"
description="We partner with leading organizations to advance diagnostic precision."
/>
</div>
<div id="social" data-section="social">
<SocialProofOne
textboxLayout="default"
useInvertedBackground={true}
names={["HealthCare System", "Medical Research Lab", "Clinical Diagnostic Corp", "Biotech Systems", "Wellness Analytics", "Digital Health Partners", "Patient Care Analytics"]}
title="Trusted by Healthcare Innovators"
description="We partner with leading organizations to advance diagnostic precision."
/>
</div>
<div id="contact" data-section="contact">
<ContactCTA
useInvertedBackground={false}
background={{
variant: "sparkles-gradient",
}}
tag="Get Started"
title="Ready to Deploy the Engine?"
description="Join the future of diagnostic health-tech."
buttons={[
{
text: "Contact Our Engineering Team",
href: "#",
},
]}
/>
</div>
<div id="contact" data-section="contact">
<ContactCTA
useInvertedBackground={false}
background={{ variant: "sparkles-gradient" }}
tag="Get Started"
title="Ready to Deploy the Engine?"
description="Join the future of diagnostic health-tech."
buttons={[{ text: "Contact Our Engineering Team", 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>
<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>
);