AI in medical field 2025 2026 applications diagnosis treatment

demonetisation India 2016 impact healthcare medical sector

mkdir -p /home/daytona/workspace/seminar-presentations

~/seminar-presentations/ai_medical.js

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const pres = new pptxgen();
pres.layout = "LAYOUT_16x9";
pres.title = "AI in the Medical Field";
pres.author = "Seminar Presentation";

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// ═══════════════════════════════════════════════════════
//  SLIDE 1 – TITLE SLIDE
// ═══════════════════════════════════════════════════════
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// ═══════════════════════════════════════════════════════
//  SLIDE 2 – AGENDA
// ═══════════════════════════════════════════════════════
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const agendaItems = [
  { num: "01", label: "Introduction & What is AI?" },
  { num: "02", label: "AI in Medical Diagnostics" },
  { num: "03", label: "AI in Drug Discovery & Research" },
  { num: "04", label: "AI in Surgical & Clinical Care" },
  { num: "05", label: "AI in Radiology & Pathology" },
  { num: "06", label: "Electronic Health Records & Administration" },
  { num: "07", label: "Ethical Challenges & Limitations" },
  { num: "08", label: "The Future of AI in Medicine" },
];
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// ═══════════════════════════════════════════════════════
//  SLIDE 3 – SECTION 01: Introduction
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 1, "Introduction", "What is Artificial Intelligence?");

// ═══════════════════════════════════════════════════════
//  SLIDE 4 – What is AI?
// ═══════════════════════════════════════════════════════
contentSlide(pres, "What is Artificial Intelligence?", [
  { text: "AI = systems that simulate human cognition: learning, reasoning, problem-solving, perception", bold: true },
  "Key subfields relevant to medicine:",
  { text: "Machine Learning (ML): algorithms that learn patterns from data without explicit programming", sub: true },
  { text: "Deep Learning: neural networks with multiple layers – excels at image and speech recognition", sub: true },
  { text: "Natural Language Processing (NLP): understanding and generating human language", sub: true },
  { text: "Computer Vision: interpreting images and video – critical for radiology and pathology", sub: true },
  "In healthcare, AI integrates with Electronic Health Records (EHRs), medical imaging, genomics, and clinical decision-support systems",
  "Global AI healthcare market: estimated USD $148 billion by 2029 (growing at ~48% CAGR)"
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 5 – SECTION 02: Diagnostics
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 2, "AI in Medical Diagnostics", "Faster, more accurate clinical decisions");

// ═══════════════════════════════════════════════════════
//  SLIDE 6 – Diagnostics content
// ═══════════════════════════════════════════════════════
contentSlide(pres, "AI-Powered Diagnostics", [
  { text: "Disease Detection & Classification", bold: true },
  { text: "DermAI: detects melanoma from dermoscopy images with accuracy matching dermatologists", sub: true },
  { text: "EchoNext (Nature, 2025): outperformed cardiologists at detecting heart disease from ECGs on 1 million+ scans", sub: true },
  { text: "Google DeepMind: detects diabetic retinopathy & age-related macular degeneration from retinal photos", sub: true },
  { text: "Predictive Diagnostics", bold: true },
  { text: "Sepsis prediction models give 6-12 hours advance warning before clinical deterioration", sub: true },
  { text: "AI-based stroke risk scoring integrates imaging + lab + ECG data for early intervention", sub: true },
  { text: "NLP models extract diagnostic clues from unstructured clinical notes", sub: true },
  "GatorTron (UF Health + NVIDIA): interprets complex clinical data for faster medical decisions"
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 7 – SECTION 03: Drug Discovery
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 3, "AI in Drug Discovery & Research", "From years to months");

// ═══════════════════════════════════════════════════════
//  SLIDE 8 – Drug Discovery
// ═══════════════════════════════════════════════════════
contentSlide(pres, "Accelerating Drug Discovery with AI", [
  { text: "Traditional drug discovery takes 10–15 years and costs USD $2.6 billion on average", bold: true },
  "AI compresses the discovery timeline to months by:",
  { text: "Generating novel molecular structures and predicting drug-target interactions", sub: true },
  { text: "Simulating how molecules behave in the human body (in silico trials)", sub: true },
  { text: "Identifying candidate compounds from vast chemical libraries in days", sub: true },
  { text: "AlphaFold 2 (DeepMind): predicted structures of 200 million+ proteins – revolutionising drug targets", bold: true },
  "MIT researchers (2025): Generative AI designed new antibiotics that cured drug-resistant infections in mice",
  "CRISPR-GPT (Stanford, 2025): AI co-pilot that designs CRISPR gene-editing experiments in months vs. years",
  "Clinical Trial Optimisation: AI identifies ideal patient populations and predicts trial dropout rates"
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 9 – SECTION 04: Surgery & Clinical Care
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 4, "AI in Surgical & Clinical Care", "Robotic precision and clinical decision support");

// ═══════════════════════════════════════════════════════
//  SLIDE 10 – Surgical AI (two-column)
// ═══════════════════════════════════════════════════════
twoColSlide(pres,
  "AI in Surgery & Clinical Decision Support",
  "Robotic Surgery", [
    "Da Vinci Surgical System: AI-enhanced robotic platform for minimally invasive procedures",
    "Augmented reality headsets for real-time anatomical overlay during operations",
    "AI tracks surgical instrument movements to identify sub-optimal technique",
    "Reduced complication rates and shorter hospital stays demonstrated in multiple trials"
  ],
  "Clinical Decision Support", [
    "AI clinical co-pilots synthesise patient history, labs, imaging, and vitals in real time",
    "Sepsis, AKI, and deterioration alerts with lead time of hours before clinical signs",
    "AI ambient scribes record and summarise patient consultations – reducing physician documentation burden by ~30%",
    "Medication error detection: AI flags dangerous interactions and dosing errors"
  ]
);

// ═══════════════════════════════════════════════════════
//  SLIDE 11 – SECTION 05: Radiology & Pathology
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 5, "AI in Radiology & Pathology", "Seeing beyond the human eye");

// ═══════════════════════════════════════════════════════
//  SLIDE 12 – Radiology & Pathology
// ═══════════════════════════════════════════════════════
contentSlide(pres, "AI in Radiology & Digital Pathology", [
  { text: "Radiology", bold: true },
  { text: "AI detects pulmonary nodules on CT with sensitivity >95%, reducing false negatives", sub: true },
  { text: "Chest X-ray AI (CheXNet, Stanford): 14 pathologies detected at radiologist-level accuracy", sub: true },
  { text: "Breast cancer screening: AI reduces unnecessary biopsies by 30% while maintaining sensitivity", sub: true },
  { text: "Targeted drugs + precision imaging enabling one-step cancer diagnosis and treatment (2026)", sub: true },
  { text: "Digital Pathology", bold: true },
  { text: "Whole-slide image analysis: AI grades tumours and identifies mitotic figures faster than pathologists", sub: true },
  { text: "Prostate cancer Gleason grading: AI matches expert pathologist performance", sub: true },
  { text: "AI reduces inter-observer variability – a longstanding problem in histopathology reporting", sub: true },
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 13 – SECTION 06: EHR & Administration
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 6, "EHR & Administrative AI", "Reducing physician burnout");

// ═══════════════════════════════════════════════════════
//  SLIDE 14 – EHR content
// ═══════════════════════════════════════════════════════
contentSlide(pres, "AI in Electronic Health Records & Administration", [
  { text: "Physician Burnout: 50% of doctors report burnout; documentation takes 2+ hours per shift above clinical time", bold: true },
  "AI Ambient Scribes (e.g. Nuance DAX, Nabla Copilot): listen, transcribe, and auto-complete clinical notes",
  "Predictive scheduling: AI reduces no-show rates and optimises clinic flow",
  "Automated ICD & CPT coding reduces billing errors and revenue leakage",
  { text: "Telemedicine + AI Triage", bold: true },
  { text: "Saudi Arabia launched world's first fully virtual hospital (2025): 130 clinics, 400,000 patients/year", sub: true },
  { text: "Symptom-checker AI directs patients to the right level of care (GP vs ED vs self-care)", sub: true },
  "AI predicted hospital savings of USD $900 billion globally by 2050 (Morgan Stanley, 2025)"
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 15 – SECTION 07: Ethics & Challenges
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 7, "Ethical Challenges & Limitations", "What clinicians must know");

// ═══════════════════════════════════════════════════════
//  SLIDE 16 – Ethics (two-column)
// ═══════════════════════════════════════════════════════
twoColSlide(pres,
  "Ethical Challenges & Limitations of Medical AI",
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    "Algorithmic bias: AI trained on non-diverse datasets can underperform for minority populations",
    "Explainability (Black Box): many deep learning models cannot explain their decisions",
    "Data privacy & HIPAA/GDPR compliance: patient data must be protected",
    "Regulatory gaps: FDA approval pathways for AI as a medical device are still evolving",
    "Over-reliance: clinicians may anchor on AI output and miss atypical presentations"
  ],
  "Safeguards & Solutions", [
    "Diverse, representative training datasets with prospective validation",
    "Explainable AI (XAI) frameworks: SHAP, LIME, attention maps",
    "Federated learning: train models across hospitals without sharing raw patient data",
    "Human-in-the-loop: AI as a second opinion, not a replacement for the clinician",
    "Continuous post-market surveillance and performance monitoring"
  ],
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);

// ═══════════════════════════════════════════════════════
//  SLIDE 17 – SECTION 08: Future
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 8, "The Future of AI in Medicine", "2026 and beyond");

// ═══════════════════════════════════════════════════════
//  SLIDE 18 – Future content
// ═══════════════════════════════════════════════════════
contentSlide(pres, "The Future of AI in Medicine", [
  { text: "Precision Medicine: AI integrates genomics, proteomics, microbiome and lifestyle data to predict disease years before symptoms", bold: true },
  { text: "Early prediction of Alzheimer's, kidney disease, and cancer with targeted interventions", sub: true },
  "Agentic AI: autonomous AI agents that manage patient follow-up, order appropriate tests, and triage results",
  "Quantum computing will allow molecular-level disease modelling and drug simulation",
  { text: "Personalised CRISPR therapies designed by AI – first-ever administered to a child in 2025", bold: true },
  "Digital twins: AI simulates an individual patient's physiology to test treatments virtually before administration",
  "AI-driven global health equity: democratising specialist-level diagnostics in low-resource settings",
  "The clinician of the future: a human-AI partnership – where empathy, judgment and AI analysis combine"
], { light: false });

// ═══════════════════════════════════════════════════════
//  SLIDE 19 – SUMMARY / THANK YOU
// ═══════════════════════════════════════════════════════
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s19.addText("KEY TAKEAWAYS", { x: 0.6, y: 0.3, w: 8, h: 0.5, fontSize: 13, bold: true, color: ACCENT, charSpacing: 5 });
const takeaways = [
  "AI is transforming every domain of medicine – from diagnostics to drug discovery",
  "Accuracy of AI often matches or exceeds specialists in narrow, well-defined tasks",
  "The greatest near-term impact is in reducing physician administrative burden",
  "Ethical guardrails, diverse data, and regulatory oversight are non-negotiable",
  "The future clinician will be a thoughtful partner with AI – not replaced by it"
];
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// ─── WRITE FILE ──────────────────────────────────────────────────
pres.writeFile({ fileName: "/home/daytona/workspace/seminar-presentations/AI_in_Medical_Field.pptx" })
  .then(() => console.log("AI presentation created successfully."))
  .catch(e => { console.error(e); process.exit(1); });

~/seminar-presentations/demonetisation.js

const pptxgen = require("pptxgenjs");

const pres = new pptxgen();
pres.layout = "LAYOUT_16x9";
pres.title = "Demonetisation – Impact & Analysis";
pres.author = "Seminar Presentation";

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  sl.addText(leftItems.map(t => ({ text: t, options: { bullet: { type: "bullet", code: "25B8" }, breakLine: true, fontSize: 13, color: "FDDBA0", paraSpaceAfter: 4 } })),
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  sl.addShape(pres.ShapeType.rect, { x: 5.3, y: 1.15, w: 4.3, h: 4.2, fill: { color: "1E0A00" }, line: { color: rightColor || GREEN_ACC, width: 1 } });
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  sl.addText(rightItems.map(t => ({ text: t, options: { bullet: { type: "bullet", code: "25B8" }, breakLine: true, fontSize: 13, color: "FDDBA0", paraSpaceAfter: 4 } })),
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  return sl;
}

// ═══════════════════════════════════════════════════════
//  SLIDE 1 – TITLE SLIDE
// ═══════════════════════════════════════════════════════
const s1 = pres.addSlide();
s1.addShape(pres.ShapeType.rect, { x: 0, y: 0, w: 10, h: 5.625, fill: { color: DARK_BG } });
s1.addShape(pres.ShapeType.rect, { x: 0, y: 3.8, w: 10, h: 0.06, fill: { color: ACCENT } });
s1.addShape(pres.ShapeType.rect, { x: 0, y: 3.88, w: 10, h: 0.04, fill: { color: ACCENT2 } });
s1.addText("₹", { x: 3.5, y: -0.8, w: 6, h: 5, fontSize: 220, bold: true, color: ACCENT, transparency: 88 });
s1.addText("DEMONETISATION", { x: 0.6, y: 1.0, w: 9, h: 0.7, fontSize: 13, bold: true, color: ACCENT, charSpacing: 5 });
s1.addText("Impact, Analysis & Lessons", { x: 0.6, y: 1.65, w: 9, h: 1.2, fontSize: 42, bold: true, color: WHITE });
s1.addText("India's Currency Overhaul of November 8, 2016 – Implications for Healthcare and Society", {
  x: 0.6, y: 2.85, w: 9, h: 0.6, fontSize: 15, color: "D4A870", italic: true
});
s1.addText("A Seminar Presentation  |  July 2026", { x: 0.6, y: 4.9, w: 5, h: 0.45, fontSize: 13, color: ACCENT2 });

// ═══════════════════════════════════════════════════════
//  SLIDE 2 – AGENDA
// ═══════════════════════════════════════════════════════
const s2 = pres.addSlide();
s2.addShape(pres.ShapeType.rect, { x: 0, y: 0, w: 10, h: 5.625, fill: { color: DARK_BG } });
s2.addText("AGENDA", { x: 0.5, y: 0.3, w: 9, h: 0.6, fontSize: 13, bold: true, color: ACCENT, charSpacing: 5 });
const agendaItems = [
  { num: "01", label: "What is Demonetisation?" },
  { num: "02", label: "Historical Context in India" },
  { num: "03", label: "The 2016 Announcement" },
  { num: "04", label: "Objectives of Demonetisation" },
  { num: "05", label: "Impact on the Indian Economy" },
  { num: "06", label: "Impact on Healthcare & Medical Sector" },
  { num: "07", label: "Impact on Agriculture & Informal Sector" },
  { num: "08", label: "Outcomes, Lessons & Way Forward" },
];
agendaItems.forEach((item, i) => {
  const col = i < 4 ? 0 : 1;
  const row = i % 4;
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  s2.addText(item.label, { x: xBase + 0.65, y: 1.12 + row * 1.0, w: 4.3, h: 0.5, fontSize: 15, color: WHITE, valign: "middle" });
});

// ═══════════════════════════════════════════════════════
//  SLIDE 3 – SECTION 01
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 1, "What is Demonetisation?", "Definition & Concept");

// ═══════════════════════════════════════════════════════
//  SLIDE 4 – Definition
// ═══════════════════════════════════════════════════════
contentSlide(pres, "Demonetisation – Definition & Concept", [
  { text: "Demonetisation: the process by which a government withdraws legal tender status from existing currency notes", bold: true },
  "The withdrawn currency must be deposited in banks or exchanged for new legal tender by a specified deadline",
  "Reasons governments demonetise currency:",
  { text: "Combat black money / tax evasion and undeclared wealth", sub: true },
  { text: "Counter counterfeit currency circulation", sub: true },
  { text: "Promote a digital, cashless economy", sub: true },
  { text: "Curb terrorist financing and illegal activity", sub: true },
  "Demonetisation is a blunt macroeconomic instrument – its success depends heavily on planning and execution",
  "Healthcare angle: India's healthcare system is predominantly cash-based, making it especially vulnerable"
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 5 – SECTION 02: Historical Context
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 2, "Historical Context in India", "Three episodes of demonetisation");

// ═══════════════════════════════════════════════════════
//  SLIDE 6 – History
// ═══════════════════════════════════════════════════════
contentSlide(pres, "India's Demonetisation History", [
  { text: "1st Demonetisation – January 12, 1946", bold: true },
  { text: "₹1,000 and ₹10,000 notes withdrawn; limited public impact as these were not in common use", sub: true },
  { text: "2nd Demonetisation – January 16, 1978", bold: true },
  { text: "₹1,000, ₹5,000, and ₹10,000 notes demonetised under the Janata Party government", sub: true },
  { text: "Affected a very small fraction of currency in circulation; relatively smooth transition", sub: true },
  { text: "3rd Demonetisation – November 8, 2016 (Most Impactful)", bold: true },
  { text: "₹500 and ₹1,000 notes declared invalid – representing 86% of all currency in circulation", sub: true },
  { text: "Announced without prior public notice – created an immediate and severe cash shortage nationwide", sub: true },
  { text: "An estimated ₹15.44 lakh crore worth of notes were invalidated overnight", sub: true },
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 7 – SECTION 03: The 2016 Announcement
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 3, "The 2016 Announcement", "November 8, 2016 – 8:00 PM broadcast");

// ═══════════════════════════════════════════════════════
//  SLIDE 8 – The Announcement
// ═══════════════════════════════════════════════════════
contentSlide(pres, "The November 8, 2016 Announcement", [
  { text: "PM Narendra Modi announced at 8 PM in a televised address that ₹500 and ₹1,000 notes would cease to be legal tender by midnight", bold: true },
  "Key operational rules announced:",
  { text: "Notes could be deposited in bank accounts until December 30, 2016", sub: true },
  { text: "Over-the-counter exchange limit: ₹4,000 per person (later revised to ₹2,000)", sub: true },
  { text: "ATM withdrawal limits: ₹2,000 per day initially; later raised to ₹4,500/week", sub: true },
  "New ₹500 and ₹2,000 notes introduced; the ₹2,000 note was a new denomination",
  "Total currency demonetised: ₹15.44 lakh crore – approximately USD $230 billion",
  { text: "Public response: long queues at banks and ATMs; reports of panic, distress and deaths linked to the cash crunch", bold: true },
  "International airports allowed exchange of up to ₹5,000 for foreign travellers"
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 9 – SECTION 04: Objectives
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 4, "Objectives of Demonetisation", "Stated goals of the policy");

// ═══════════════════════════════════════════════════════
//  SLIDE 10 – Objectives (two-column)
// ═══════════════════════════════════════════════════════
twoColSlide(pres,
  "Stated Objectives of Demonetisation 2016",
  "Primary Goals", [
    "Eliminate black money stored as cash outside the banking system",
    "Flush out counterfeit Indian currency notes (FICN) funding terrorism and naxalism",
    "Broaden the tax base – bring the informal economy into formal financial records",
    "Promote Digital India: accelerate shift to mobile payments, UPI, and digital wallets",
    "Curb corruption and reduce the shadow economy (estimated at 20–25% of GDP)"
  ],
  "Secondary / Aspirational Goals", [
    "Reduce real estate price inflation driven by unaccounted cash transactions",
    "Improve fiscal position: increased tax compliance and direct tax revenues",
    "Disrupt Hawala and illegal money networks",
    "Accelerate financial inclusion: bring unbanked population into formal banking",
    "Reduce counterfeit notes used for terror financing along border regions"
  ],
  "C44D28", "1A8070"
);

// ═══════════════════════════════════════════════════════
//  SLIDE 11 – SECTION 05: Economic Impact
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 5, "Impact on the Indian Economy", "GDP, employment and banking");

// ═══════════════════════════════════════════════════════
//  SLIDE 12 – Economic Impact
// ═══════════════════════════════════════════════════════
contentSlide(pres, "Macroeconomic Impact", [
  { text: "Short-Term GDP Shock", bold: true },
  { text: "Economic activity reduced by at least 3 percentage points in Nov–Dec 2016 (NBER, Chodorow-Reich et al.)", sub: true },
  { text: "India's GDP growth fell to 6.1% in Q4 FY2016-17 vs forecast of 7.1% – first sub-7% since June 2011", sub: true },
  { text: "RBI dividend to government: only ₹32,000 crore in 2016-17 vs ₹52,000 crore in 2015-16 (extra printing costs)", sub: true },
  { text: "Employment", bold: true },
  { text: "Quarterly employment growth declined by 2 percentage points (NBER study)", sub: true },
  { text: "SME sector severely impacted – cash-dependent small businesses faced closure and job losses", sub: true },
  { text: "Tax Base (Positive)", bold: true, green: true },
  { text: "9.1 million new taxpayers added; significant increase in income tax returns filed post-demonetisation", sub: true },
  { text: "Digital transactions surged: UPI transactions grew from near-zero to billions per month", sub: true },
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 13 – SECTION 06: Healthcare Impact
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 6, "Impact on Healthcare", "A sector unprepared for a cash crisis");

// ═══════════════════════════════════════════════════════
//  SLIDE 14 – Healthcare impact (two-column)
// ═══════════════════════════════════════════════════════
twoColSlide(pres,
  "Impact on the Healthcare & Medical Sector (BMJ Global Health, 2020)",
  "Negative Impacts", [
    "Drop in outpatient visits and hospital admissions at multiple centres",
    "Elective surgeries postponed – patients unable to access cash for pre-payments",
    "Reduced antenatal care visits in early demonetisation period",
    "Rural patients worst affected – over 70% of India's healthcare accessed via cash-based private sector",
    "Delayed emergency presentations correlated with the cash crunch period",
    "Medical shops and pharmacies faced stock shortages as supply chain payments disrupted"
  ],
  "Adaptive Responses", [
    "Government hospitals accepted old notes for a transition period",
    "Many private hospitals adopted card/digital payments earlier than planned",
    "Non-cash transactions rose significantly – not-for-profit hospitals less financially impacted",
    "Income at not-for-profit hospitals not significantly reduced (BMJ study) due to charity/welfare funds",
    "Digital health records and cashless insurance adoption accelerated",
    "Telemedicine consultations increased as an alternative to cash-heavy in-person visits"
  ]
);

// ═══════════════════════════════════════════════════════
//  SLIDE 15 – SECTION 07: Agriculture & Informal Sector
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 7, "Agriculture & Informal Sector", "The hardest-hit communities");

// ═══════════════════════════════════════════════════════
//  SLIDE 16 – Agriculture content
// ═══════════════════════════════════════════════════════
contentSlide(pres, "Impact on Agriculture, Rural Areas & Informal Sector", [
  { text: "Agriculture sector (70% of population depends on it): almost entirely cash-based at the transactional level", bold: true },
  { text: "Farmers unable to purchase seeds, fertilisers, and equipment in the sowing season of Rabi 2016-17", sub: true },
  { text: "Agri-commodity markets disrupted; perishable produce prices crashed as buyers lacked cash", sub: true },
  { text: "Cement production contracted 8.7% in Nov 2016 and 13.3% in Dec 2016 (construction sector)", bold: true },
  "Informal / Unorganised Sector (~45% of GDP):",
  { text: "Daily wage labourers, domestic workers, street vendors faced sudden income loss", sub: true },
  { text: "A Parliamentary panel report (April 2017): rural households and honest taxpayers were 'worst hit'", sub: true },
  { text: "Q3 new investment proposals at a decade low; services sector adversely impacted", sub: true },
  { text: "By March 2017: new currency = 77% of old value; by June 2017, shortage mostly resolved (NBER)", bold: true },
]);

// ═══════════════════════════════════════════════════════
//  SLIDE 17 – SECTION 08: Outcomes & Lessons
// ═══════════════════════════════════════════════════════
sectionSlide(pres, 8, "Outcomes, Lessons & Way Forward", "What did demonetisation achieve?");

// ═══════════════════════════════════════════════════════
//  SLIDE 18 – Outcomes (two-column)
// ═══════════════════════════════════════════════════════
twoColSlide(pres,
  "Did Demonetisation Achieve Its Goals?",
  "Limited/Contested Outcomes", [
    "99.3% of demonetised currency returned to banks – RBI data showed almost no black money was destroyed",
    "Counterfeit currency continued in new denominations – goal only partially met",
    "Terror and naxalism saw short-term reduction but returned to prior levels",
    "Carried out 'without prior study or research' – Parliamentary Panel, April 2017",
    "Long-term black money habits not permanently curbed",
  ],
  "Positive Outcomes", [
    "Digital payments ecosystem transformed: UPI became a global benchmark for real-time payments",
    "Tax base expanded: 9.1 million new taxpayers registered",
    "Banking penetration improved in semi-urban and rural areas",
    "India Post Payments Bank and Jan Dhan accounts activated en masse",
    "Healthcare sector began shift toward digital and cashless transactions",
    "Increased awareness of financial inclusion and formal economy benefits"
  ]
);

// ═══════════════════════════════════════════════════════
//  SLIDE 19 – Way Forward for Healthcare
// ═══════════════════════════════════════════════════════
contentSlide(pres, "Lessons for Healthcare Policy Makers", [
  { text: "Healthcare must be insulated from sudden macro-economic shocks", bold: true },
  "Policy recommendation: mandate cashless payment infrastructure in all private healthcare facilities before emergency policy changes",
  "Maintain emergency cash reserves or voucher systems for rural primary care during monetary disruptions",
  { text: "Digital health infrastructure investment is a strategic necessity – not a luxury", bold: true },
  { text: "EHRs, UPI-based hospital billing, and telemedicine platforms reduce vulnerability to cash crises", sub: true },
  "Health insurance penetration must increase: only 36% of India covered by any form of health insurance (2024)",
  { text: "Key lesson: policies affecting monetary systems must include healthcare sector impact assessments", bold: true },
  "AI and digital health can serve as a bridge – reducing reliance on cash transactions while improving access to care"
], { light: false });

// ═══════════════════════════════════════════════════════
//  SLIDE 20 – THANK YOU
// ═══════════════════════════════════════════════════════
const s20 = pres.addSlide();
s20.addShape(pres.ShapeType.rect, { x: 0, y: 0, w: 10, h: 5.625, fill: { color: DARK_BG } });
s20.addShape(pres.ShapeType.rect, { x: 0, y: 3.85, w: 10, h: 0.06, fill: { color: ACCENT } });
s20.addShape(pres.ShapeType.rect, { x: 0, y: 3.93, w: 10, h: 0.04, fill: { color: ACCENT2 } });
s20.addText("KEY TAKEAWAYS", { x: 0.6, y: 0.3, w: 8, h: 0.5, fontSize: 13, bold: true, color: ACCENT, charSpacing: 5 });
const takeaways = [
  "Demonetisation 2016 was the most disruptive monetary policy in modern Indian history",
  "86% of currency invalidated overnight – healthcare, agriculture and informal sectors suffered most",
  "Digital payments transformation: UPI emerged as India's landmark fintech success post-demonetisation",
  "Healthcare must have cashless contingency infrastructure to prevent access gaps during monetary disruptions",
  "Policy interventions require prior research and phased rollout to minimise human suffering"
];
takeaways.forEach((t, i) => {
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});
s20.addText("Thank You", { x: 0.6, y: 4.8, w: 5, h: 0.55, fontSize: 22, bold: true, color: ACCENT2 });
s20.addText("Questions & Discussion", { x: 5.5, y: 4.85, w: 4, h: 0.45, fontSize: 14, color: "D4A870", align: "right" });

// ─── WRITE FILE ──────────────────────────────────────────────────
pres.writeFile({ fileName: "/home/daytona/workspace/seminar-presentations/Demonetisation.pptx" })
  .then(() => console.log("Demonetisation presentation created successfully."))
  .catch(e => { console.error(e); process.exit(1); });

cd /home/daytona/workspace/seminar-presentations && node ai_medical.js && node d…

ls -lh /home/daytona/workspace/seminar-presentations/*.pptx

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cd /home/daytona/workspace/seminar-presentations && node demonetisation.js