AI for Better Health

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When I was eight, I got thrown from a horse.

My dad—true to cowboy form—told me to get back in the saddle.

I did, using a picnic table as a mount since I couldn’t move my arm. The ER said I was fine. But by Monday, the radiologist called—my arm was broken.

Not life-threatening, but I spent the weekend in unnecessary pain because the diagnosis was delayed.

That same dynamic—delayed or missed diagnosis—plays out in healthcare daily, but with far higher stakes.

Each year in the U.S., over 795,000 people suffer death or permanent disability due to diagnostic errors. Many are preventable.

This is where AI moves from hype to critical infrastructure. AI shouldn’t replace physicians—it should augment them. What it is adept at is catching what they might miss, flagging it earlier, and delivering answers faster.

☕️ AI Tangle - DeepSeek's Stealth R1 Update, xAI's $300M Telegram Deal & The NYT's First AI Deal with Amazon

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🎯 The AI Marketing Advantage - Google’s Veo 3 Is Breaking the Internet

💡 AI CIO - New NIST Metric Could Tackle AI Vulnerabilities

🎙️ AI Confidential Podcast - On the Cutting Edge of Agentic AI with João Moura

 📚 AIOS - This is an evolving project. I started with a 14-day free Al email course to get smart on Al. But the next evolution will be a ChatGPT Super-user Course and a course on How to Build Al Agents.

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AI For Better Health

How AI Is Saving Lives, Cutting Costs, and Catching What Humans Miss

Most people use AI to write better blog posts or analyze spreadsheets. Helpful, sure—but not exactly high stakes.

In healthcare, the stakes are real. Lives are on the line. That’s why I’m especially interested in how AI can improve diagnosis, treatment, and patient outcomes.

While AI adoption is impacting every aspect of our work lives, if you’re in the medical field, there are some great improvements worth watching.

Unlike productivity use cases, healthcare applications demand a higher standard of accuracy, safety, and ethical oversight. A flawed AI-generated paragraph won’t harm anyone. A flawed AI-generated diagnosis might.

That’s why the integration of artificial intelligence in healthcare requires more than just technical innovation—it demands clinical validation, regulatory scrutiny, and trust from both providers and patients.

The potential for AI improvements in health care and life sciences is enormous. From early disease detection and personalized medicine to operational efficiency in hospitals, AI can augment—not replace—medical professionals in ways that lead to better, faster, and more equitable care. The key is applying these tools with rigor, transparency, and human oversight.

The Universal AI Capabilities

AI excels at a few fundamental cognitive tasks that mirror how humans process information, but at superhuman scale and speed. These capabilities are domain-agnostic—they work the same whether you're analyzing numbers, images, text, or sensor data.

Pattern Recognition & Anomaly Detection

AI's most fundamental ability is finding meaningful patterns in complex data while simultaneously identifying when something doesn't fit the expected pattern. It's like having a detective who can instantly spot subtle connections across millions of data points that would take humans years to notice. The AI learns what "normal" looks like, then flags anything that deviates significantly from that baseline.

Predictive Analytics & Forecasting

By analyzing historical patterns, AI can project future scenarios with remarkable accuracy.  It’s not magic—it’s sophisticated statistical modeling that identifies trends, cycles, and relationships in data to make educated predictions about what's likely to happen next. The more data it has, the more accurate these predictions become.

Automation & Process Optimization

AI can take repetitive, rule-based tasks and execute them faster and more consistently than humans. But beyond simple automation, it can also optimize complex processes by finding the most efficient paths, timing, and resource allocation. It's like having a tireless worker who also continuously improves at the job.

Enhanced Decision-Making & Analysis

Perhaps most powerfully, AI can synthesize large amounts of information to support better decision-making. It can weigh multiple variables simultaneously, consider scenarios humans might miss, and provide data-driven insights that cut through complexity and uncertainty.

The Evolution from Specialized to Universal

I used to think we'd see an explosion of highly specialized AI models for every industry and use case. Now I believe we're seeing a different pattern emerge: specialized models serve as proof-of-concept laboratories that demonstrate what's possible in specific domains, then their capabilities get absorbed into larger, more general models.

Think of specialized models as the R&D departments of AI—they push the boundaries in narrow areas, prove viability, and develop the techniques. But the real power comes when those innovations get integrated into general-purpose models that can apply the same learned capabilities across multiple domains simultaneously.

How These Translate Across Domains

In Business Settings:

• Pattern recognition spots market trends, customer behavior shifts, and operational inefficiencies

• Predictive analytics forecasts sales, demand, and risk scenarios

• Automation streamlines workflows, customer service, and data processing

• Enhanced analysis informs strategic decisions and competitive positioning

In Healthcare:

• Pattern recognition catches disease symptoms humans miss, enabling earlier intervention

• Predictive analytics anticipates patient deterioration, appointment patterns, and treatment outcomes

• Automation handles documentation, routine processes, and administrative tasks

• Enhanced analysis supports diagnosis, treatment planning, and research breakthroughs

The Universal Truth

The same pattern recognition that identifies profitable customers in business and disease symptoms in healthcare also spots security threats in cybersecurity, identifies promising research directions in academia, flags equipment failures in manufacturing, and detects learning difficulties in education.

This convergence toward universal models makes sense—rather than maintaining dozens of specialized tools, organizations can leverage one powerful system that understands their specific domain context while drawing from capabilities proven across all fields.

AI for Diagnostics, See Earlier, Act Faster

At UC San Diego Health, an AI early warning system continuously scans vital signs and lab data to detect sepsis—a deadly, fast-moving infection—before it escalates. The result: a 17% drop in sepsis-related mortality.

In radiology, AI is already outperforming humans in spotting subtle signs of disease. These findings suggest that AI enhances early detection of clinically relevant breast cancer and reduces the screen-reading workload—all without increasing false positives.

In a study conducted in Denmark, AI-assisted screening detected more breast cancers (0.82% vs. 0.70%) and reduced the false-positive rate (1.63% vs. 2.39%) compared to traditional screening methods—an impactful improvement.

The U.S. Food and Drug Administration (FDA) has now cleared over 1,000 AI algorithms for commercial use. Radiology dominates the field, accounting for 758 approvals—roughly 76% of all cleared clinical AI.

Cardiology ranks second with 161 clearances, some spanning multiple specialties. Neurology follows distantly, with 35 AI tools approved. Beyond those, AI is slowly making inroads across 15 other specialties, each with fewer than 20 FDA-cleared algorithms to date.

Drug Discovery, AI Compressing the Timeline

Developing a new drug usually takes a decade and costs over $2 billion. AI is collapsing that timeline. UK-based Exscientia created the first AI-designed drug to enter clinical trials in just 12 months—a compound targeting obsessive-compulsive disorder.

Since then, multiple AI-discovered molecules have advanced to human trials. One targeting idiopathic pulmonary fibrosis is already in Phase II trials in the U.S. and China.

Meanwhile, DeepMind’s AlphaFold released a public database predicting the 3D structure of over 200 million proteins, accelerating drug target discovery for researchers worldwide.

Early data shows that AI-designed compounds may have double the success rate in Phase I trials compared to traditional candidates. The implications: faster pipelines, lower costs, and more shots on goal.

Clinical Operations, Efficiency That Impacts Outcomes

AI is also reshaping care delivery at the operational level. At Cedars-Sinai, AI triage tools helped reduce length of stay by 12–26% for patients with serious conditions like stroke or pulmonary embolism.

At NYU Langone, GPT-4 was used to review and improve physician notes. That project led to a 19% shorter length of stay and up to 15% better mortality outcomes for patients in pilot departments.

Kaiser Permanente rolled out an AI-powered ambient scribe system that quietly handles documentation in the background. Over 7,000 physicians used it across 2 million visits, saving 15,700 hours of physician time and significantly reducing after-hours charting. Eighty-four percent of doctors said it improved their ability to focus on patients.

Patient Engagement: Always-On, Cost-Effective Care

AI is also extending care beyond clinic walls. At UMass Memorial Health, a remote monitoring system for heart failure patients reduced readmissions by 50%, using AI to flag concerning trends in daily vitals and symptoms.

The UK’s NHS used AI to predict no-shows and optimize scheduling. The result: a 30% drop in missed appointments, freeing up thousands of visits annually and saving an estimated £27 million.

Mental health clinics are seeing similar gains. One major provider used the Limbic AI chatbot to automate intake, increasing successful referrals by 30% and saving 3,000 clinician hours per year—the workload of four full-time staff.

The Big Impact Beyond IT

AI is moving from novelty tools like ChatGPT to real life-saving technology—today, it multiplies results across virtually every medical function. It is increasing diagnostic accuracy, reducing time to treatment, cutting costs, and freeing up clinicians to focus on care.

Organizations integrating AI at the operational level are outperforming peers on cost, quality, and staffing resilience. The risk isn’t adoption—it’s delay.

AI is already in the ER, the imaging suite, the R&D pipeline, and the patient’s living room. It’s catching what humans miss and accelerating what humans do best.

• Cal AI - An AI-powered nutrition app that automates meal logging and analysis via photo recognition.

• Consensus AI - This tool offers doctors a specialized AI search engine to quickly find and understand research papers across a wide range of medical topics. It’s a powerful tool for doctors, enhancing their ability to find, understand, and utilize medical research effectively.

• Upheal – AI note-taking for therapists and mental health professionals, offering structured summaries and clinical insights.

• Wysa - An AI-powered mental health app that uses evidence-based cognitive behavioral therapy (CBT) techniques to provide 24/7 anonymous support, with escalation to human therapists when needed.

• Skinive AI – An AI dermatologist tool that analyzes skin images to identify moles, rashes, and other potential issues for early intervention and monitoring.

ChatGPT-Driven Health & Wellness Analysis

The included prompt can be used with any model you like. If you are concerned about your health data you can even use this with a locally running LLM.

However, you can use this health tracker as a Custom GPT to regularly track and review your health by inputting details about medications, supplements, lab tests, medical conditions, diet, exercise, and other lifestyle habits.

The GPT will summarize your inputs, offer feedback, and provide suggestions for improvement. Over time, this allows you to track progress, identify trends, and stay accountable to health goals. Just add your lab reports and other data to the Custom GPT.

However, it's important to consider privacy risks when sharing personal health information with a publicly hosted system. Health data is sensitive, and publicly available systems may not offer the same security protections as private ones. For more sensitive information, use encrypted systems or apps designed for secure health tracking. Always consult a healthcare provider for personalized advice.

The Health Analyzer Prompt

This prompt offers a comprehensive, AI-assisted way to analyze your health information. Keep in mind that you should not rely on AI for health advice, but use it as a research aid to support consultations with your medical providers.

### `⚠️ Opening Disclaimer`

> `Disclaimer: This conversation is for educational and informational purposes only. It is not a substitute for professional medical advice, diagnosis, or treatment. Always consult your healthcare provider before making changes to medications, diet, exercise, or other health routines.`
> 

---

### `Session Instructions (for GPT):`

- `Walk through the user’s **health and lifestyle history** using the sections below.`
- `After each response:`
    - `Summarize key info`
    - `Provide **pros/cons** of the user’s behaviors or health status`
    - `Suggest considerations for optimization or habit change`
    - `Wait for confirmation before moving to the next section`

---

## `🧩 Sections to Cover:`

---

### `1. **Medications**`

> `Please list all current prescription medications, OTC meds, and what they’re for. Include dosage and frequency if possible.`
> 

---

### `2. **Supplements**`

> `List all supplements (vitamins, minerals, herbs, protein powders, etc.) you take. Include brand or dosage and why you take them, if known.`
> 

---

### `3. **Lab Tests / Bloodwork**`

> `If you’ve had recent bloodwork or tests, please upload or list major results (cholesterol, glucose, thyroid, vitamin D, etc.).`
> 

---

### `4. **Medical Conditions**`

> `List any chronic or ongoing medical issues, orthopedic problems, surgeries, or significant past conditions.`
> 

---

### `5. **Allergies & Sensitivities**`

> `Do you have any allergies or intolerances (e.g., food, medication, seasonal)? Any known sensitivities?`
> 

---

### `6. **Diet Preferences**`

> `What type of diet do you follow or prefer (keto, balanced, vegetarian, Mediterranean, paleo, etc.)? Any foods you avoid or emphasize?`
> 

---

### `7. **Exercise Habits**`

> `What kind of physical activity do you currently do? Include types, frequency, preferences, and any injuries or limitations.`
> 

---

### `8. **Sleep, Stress, and Substances**`

> `How many hours do you sleep on average? How would you rate your stress level? Do you use alcohol, tobacco, or recreational drugs?`
> 

---

## `✅ Final Report: Summary & Personalized Considerations`

`Once all sections are complete, say:`

> `“Thank you for completing the health and wellness assessment. Here’s a summary of your current profile, followed by key considerations to help optimize your well-being based on the information you’ve shared.”`
> 

### `Final Report Should Include:`

1. **`Your Health Snapshot**:`
    - `Summary of medications, health conditions, and labs`
    - `Exercise and dietary patterns`
    - `Lifestyle behaviors (sleep, stress, substances)`
2. **`What You’re Doing Well** ✅`
    
    `Highlight strengths, consistency, awareness, good habits`
    
3. **`Areas for Improvement** ⚠️`
    
    `Flag concerns, risk areas, missed opportunities`
    
4. **`Recommended Behavior Changes** 🔄`
    - `Diet adjustments (e.g., improve fiber, reduce processed foods)`
    - `Exercise modifications (e.g., include mobility work, build routine)`
    - `Stress and sleep support ideas (e.g., wind-down routines, CBT-I, mindfulness)`
5. **`Trackable Goals** 🎯`
    - `Small measurable targets (e.g., “increase sleep to 7 hours/night,” “2 strength sessions per week”)`
6. **`Follow-Up Suggestions** 📅`
    - `Suggest tracking symptoms or habits weekly`
    - `Recommend labs to recheck`
    - `When to talk to a doctor`

By setting the GPT to private, turning off training data in settings, and consulting your doctor regularly, you can ensure your health data stays secure and your progress is always in line with professional advice.

I appreciate your support.