AIHealthTech Insider: Issue # 36

This week, we explore groundbreaking developments, from Mount Sinai pioneering the first AI-powered robotic system for treating enlarged prostate conditions in NYC, to AI's transformative impact on stroke risk and AFib treatment. We also delve into how AI is revolutionizing brain imaging and enzyme engineering, showcasing a future where AI isn't just an assistant but a pivotal force in medical innovation.

Mount Sinai Leads NYC with First AI-Powered Robotic System for Enlarged Prostate Treatment

Mount Sinai just made history as the first hospital in New York City to use the HYDROS™ Robotic System, an advanced AI-driven solution for treating benign prostatic hyperplasia (BPH)—a condition affecting over 50% of men over 60.

Why This Matters

Traditional treatments for BPH, like TURP and laser therapy, can come with side effects like incontinence and erectile dysfunction. HYDROS™ is different—it uses AI-powered imaging and robotic precision to remove excess prostate tissue without heat, minimizing risks and preserving key functions.

How It Works

🔹 AI-powered planning – FirstAssist AI™ maps critical structures using ultrasound, creating a personalized treatment plan for each patient.
🔹 Advanced imaging – Combines ultrasound and digital cystoscopy for a clearer, more precise surgical view.
🔹 Heat-free waterjet technology – Removes excess prostate tissue without damaging surrounding areas, reducing complications.
🔹 Robotic precision – Ensures greater accuracy and improves surgical outcomes.

Game-Changing Results

Mount Sinai’s urology team has already completed three successful procedures, with all patients discharged the next day. Dr. Steven A. Kaplan, a pioneer in robotic prostate surgery, calls HYDROS™ a major leap forward in men’s health.

What’s Next?

Mount Sinai is expanding access by training more surgeons and tracking long-term patient outcomes to further validate the system’s benefits.

👉Read more here.

AI Is Changing Stroke Risk & AFib Treatment—Here’s How

For years, treating persistent atrial fibrillation (AFib) has been a guessing game. Standard ablation works for some, but failure rates are high—especially in long-term cases.

Now, AI is flipping the script. A new randomized trial proves that AI-guided ablation is significantly more effective than the traditional “one-size-fits-all” approach.

Key Takeaways:

🔹 AI makes ablation smarter – Instead of just isolating pulmonary veins, AI pinpoints additional trouble spots, leading to an 88% success rate vs. 70% with the standard method.
🔹 Better results, same safety – Despite targeting more areas, the AI-driven approach didn’t increase risks or complications.
🔹 Biggest impact for tough cases – If AFib lasted 6+ months, AI-guided treatment was even more effective than standard ablation.
🔹 This is just the beginning – AI’s ability to analyze real-time heart activity could redefine how we treat AFib (and other heart conditions) moving forward.

This isn’t hype—it’s hard data. AI isn’t just predicting disease. It’s fixing it.

👉 Read the full study here.

AI is Transforming Brain Imaging—Here’s How

Generative AI is changing medical imaging by learning what a healthy brain looks like—no labeled data needed. Now, AI models can detect anomalies more accurately than ever.

Key Takeaways:

🔹 Smarter anomaly detection – AI trained on “normative learning” identifies a wide range of brain abnormalities.
🔹 New evaluation metrics – RQI, AHI, and CACI provide a more complete assessment of AI-generated pseudo-healthy images.
🔹 Clinical validation – Studies show AI can match expert radiologists in spotting subtle brain anomalies.
🔹 Next-gen AI models – Diffusion networks & hybrid AI architectures boost diagnostic accuracy.

This breakthrough brings AI closer to revolutionizing early disease detection, medical imaging, and personalized healthcare.

👉 Read the full study on Nature.

AI Just Built New Enzymes From Scratch—And They’re 60,000x Faster

For years, enzyme engineering has been a slow, trial-and-error process. AI has helped, but most lab-made enzymes stalled after the first reaction step—making them useless for real applications.

Now, that’s changed. Scientists used AI to create enzymes that complete multi-step reactions, just like natural ones.

Key Takeaways:

🔹 Built from scratch – No tweaking old enzymes. These were fully AI-designed for a four-step chemical reaction called serine hydrolysis (used in digestion, fat metabolism, and even plastic recycling).
🔹 Massive performance leap – The new AI-designed enzymes were 60,000 times faster than previous attempts.
🔹 How they did it – Scientists combined two AI models: RFdiffusion (to generate enzyme structures) and PLACER (to fine-tune atomic interactions at every step).
🔹 Why this matters – This breakthrough takes AI-designed enzymes one step closer to real-world use—from medicine to industrial processes.

AI isn’t just discovering new proteins—it’s building functional, life-like enzymes that could reshape biotech.

👉 Read the full study here.

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