AI-powered digital stethoscopes show promise in bridging screening gaps

(Photo: Eko Health, US) IANS

New Delhi, As tuberculosis (TB) continues as the deadliest infectious cause of deaths globally, a new study has shown that artificial intelligence (AI)-enabled digital stethoscopes can help fill critical screening gaps, especially in hard-to-reach areas.

In a commentary published in the journal Med (Cell Press), global experts contended that stethoscopes combined with digital technology and AI can be a better option against the challenges faced in screening programmes, such as under-detection, high cost, and inequitable access.

“AI-enabled digital stethoscopes have demonstrated promising accuracy and feasibility for detecting lung and cardiovascular abnormalities, with promising results in early TB studies. Training and validation in diverse, high-burden settings are essential to explore the potential of this tool further,” said corresponding author Madhukar Pai from McGill University, Canada, along with researchers from the UAE, Germany, and Switzerland.

Despite advancements in screening and diagnostic tools, an estimated 2.7 million people with TB were missed by current screening programmes, as per data from the World Health Organization (WHO). Routine symptom screening is also likely to miss people with asymptomatic or subclinical TB.

While the WHO recently recommended several AI-powered computer-aided detection (CAD) software, as well as ultra-portable radiography hardware, higher operating costs and upfront hardware act as a deterrent.

This particularly appeared difficult in primary care settings and or among pregnant women due to radiation concerns.

At the same time, AI showed significant potential for screening, including applications beyond CAD of TB from radiographs, said the researchers.

“One application of AI for disease screening is to interpret acoustic (sound) biomarkers of disease, with potential to identify sounds that appear nonspecific or are inaudible to the human ear,” they added, while highlighting the potential of AI in detecting and interpreting cough biomarkers and lung auscultation to analyse breath sounds.

Studies from high-TB burden countries, including India, Peru, South Africa, Uganda, and Vietnam, highlighted that AI-enabled auscultation could hold promise as a TB screening and triage tool.

"AI digital stethoscopes may become useful alternatives to imaging-based approaches for TB screening, with the potential to democratise access to care for populations underserved by radiography," the researchers said."Importantly, AI digital stethoscopes offer a scalable, low-cost, and person-centered tool that could bring us closer to reaching TB case finding goals," they added. AI-powered digital stethoscopes show promise in bridging screening gaps | MorungExpress | morungexpress.com

Read More........→February 12, 2026

AI tool can simulate complex fusion plasma in seconds

(Image: UKAEA)

A team of scientists from the UK Atomic Energy Authority, the Johannes Kepler University Linz, and Emmi AI, have developed an artificial intelligence tool - named GyroSwin - which can create simulations up to 1,000 times faster than traditional computational methods.

Magnetic nuclear fusion is considered a promising technology for sustainable and emission-free energy supply. However, to achieve fusion, machines need to confine plasma at extreme temperatures using powerful magnets. Managing turbulence within the plasma is a key fusion challenge so it needs to be accurately modelled.

Plasma scientists rely on state-of-the-art numerical simulations, using five-dimensional (5D) gyrokinetics, which includes three spatial dimensions plus two additional dimensions which account for parallel and perpendicular velocity of particles within the plasma. This 5D approach requires immense supercomputing power. Traditional simulations are extremely slow and computationally expensive, significantly lengthening design and development cycles. Previously, computation methods simulated a plasma by actively calculating the complex plasma dynamics.

GyroSwin uses the latest AI methods to learn the 5D simulation dynamics and the resulting surrogate models can run in seconds, in contrast to the hours or even days for conventional simulations. It was trained on six terabytes of data. This speed allows for much faster, more agile prediction of plasma turbulence, crucial for optimising fusion machine designs.

"Designing, developing, and operating a fusion power plant will involve millions of plasma simulations," said Rob Akers, Director of Computing Programmes at UKAEA. "Reducing runtimes from hours or days to minutes or seconds - whilst preserving sufficient accuracy - will be essential for making this challenge manageable. Pioneering AI-based tools like GyroSwin therefore show great promise for being genuinely transformative around time-to-solution and cost."

Processing 5D data has never previously been tackled by an AI surrogate model, and GyroSwin outperforms other AI methods it's been compared against, UKAEA noted. This increased performance is made possible because GyroSwin preserves key physical information from a fusion plasma, including the length scale of fluctuations, and the sheared flows that can reduce turbulence - all crucial to the physical interpretability of plasma simulations.

"We love scientific challenges, and building AI models that accelerate 5D gyrokinetic simulations is definitely one of the toughest challenges out there," said Johannes Brandstetter, Professor at JKU, co-founder and Chief Scientist at Emmi. "We are very proud of how far we got in this great collaboration, but we know that we have just scratched the surface."

UKAEA will now research how GyroSwin's advanced capability can be applied to next generation power plants such as the UK's Spherical Tokamak for Energy Production (STEP), where millions of simulations will potentially be required to optimise plasma scenario designs with uncertainty quantification. As more complex physics is included for power plant conditions, simulations become even more lengthy, making faster plasma modelling essential.This GyroSwin project was part-funded by the International Computing element of the UK Government's Fusion Futures Programme. AI tool can simulate complex fusion plasma in seconds

Read More........→February 11, 2026