Author: Dzmitry Korsak

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Experienced journalist and editor with over 25 years in the field. His work focuses on medical technologies, social issues, and innovation. He values an evidence-based approach, thorough work with primary sources, and the ability to communicate complex topics in a clear and accessible way.

Another unusual “side effect” has been observed with semaglutide — the drug better known as Ozempic and Wegovy. Originally developed for type 2 diabetes, it proved effective for weight reduction, and now appears to benefit treatment of certain cancers. A University of California San Diego study reports that among people with colon cancer who were concurrently taking semaglutide, five-year mortality was 15.5%, whereas among those not taking it the figure was 37.1% — more than twice as high.

AI now shows up in everyday mental-health chats—from sleep tips to suicidal disclosures—driven by poor access, stigma, and the lure of anonymous, free help. Yet LLMs are unreliable: they err, lose context, miss non-verbal cues, and can reinforce distortions. Crisis-performance evidence is thin, and the red lines remain contested.

Diagnosis of respiratory diseases through lung sounds remains one of the most complex clinical tasks. Even experienced physicians admit that auscultation results are often subjective: one specialist hears a pathology, while another does not. Yet these judgments influence critical decisions – whether to hospitalize a patient, prescribe antibiotics, or assess the severity of their condition.

The digital health market is expanding fast – IQVIA’s Digital Health Trends 2024 estimates there are roughly 337,000 health-related apps today. Behind that impressive number lies a worrying statistics: around 90% of startups never reach a market release, and of those that do, roughly 20% shut down within the first year. For developers and investors, this is a landscape full of hidden traps, where success depends not only on the strength of the idea but also on the ability to navigate dense regulatory filters.

In recent years, more and more mental-health care startups have pinned their hopes on AI, promising “therapy without the therapist.” Yet thoughtless automation often backfires: clients receive shallow support, and in crises, AI therapy apps simply don’t cope. Algorithmic errors erode trust not only in digital therapy but in AI itself.

magine that there is a model that predicts an individual’s risk of thousands of diseases based solely on their medical history. What product would you like to create based on this model? This is not a hypothetical question – such a model already exists. It is described in a recent article in Nature, is publicly available, and is waiting for a team that can put it into practice.

We see MedTech today as a structural pillar of healthcare: tests and analyzers, monitors and pumps, CT/MRI and ultrasound scans, implants and disposables, as well as software for monitoring. Europe spends nearly 1% of the EU’s GDP on it; this figure may look modest to some, but the effect is cumulative and systemic, implying further steady growth. The money goes into tools without which patient pathways often cannot even start.