Anyone waiting for the results of a medical test knows the anxious question: 'Will my life change completely when I know?' And the relief if you test negative.

Nowadays, Artificial Intelligence (AI) is deployed more and more to predict life-threatening disease. But there remains a big challenge in getting the Machine Learning (ML) algorithms precise enough.

No two human beings are the same, a biologic singularity encoded in the unique arrangement of the molecules that make up our individual DNA.

Variation is a cardinal feature of biology, the driver of diversity, and the engine of evolution, but it has a dark side. Alterations in DNA sequences and the resulting proteins that build our cells can sometimes lead to profound disruptions in physiologic function and cause disease.

For the first time, researchers at the Technical University of Munich (TUM) have successfully used a new X-ray method for respiratory diagnostics with patients. Dark-field X-rays visualize early changes in the alveolar structure caused by the lung disease COPD and require only one fiftieth of the radiation dose typically applied in X-ray computed tomography.

Scientists from Queen's University Belfast have developed a computer-aided data tool that could improve treatment for a range of illnesses.

The computer modelling tool will predict novel sites of binding for potential drugs that are more selective, leading to more effective drug targeting, increasing therapeutic efficacy and reducing side effects.

Researchers in the health and wellness space have typically relied on people to report their personal health data, like activity levels, heart rate or blood pressure, during brief snapshots in time.

Wearable health devices, such as the popular Apple Watch, have changed the game, surfacing meaningful data that can paint a more complete picture of daily life and resulting health and disease for clinicians.

In a little over 18 months, the novel coronavirus (Sars-CoV-2) has infected over 18 million people and caused more than 690,000 deaths. The current standard for diagnosis through reverse transcription polymerase chain reaction is limited owing to its low sensitivity, high rate of false positives, and long testing times. This makes it difficult to identify infected patients quickly and provide them with treatment.

Researchers are developing a program that could be added to the COVID alert app used on smartphones to better target vaccination campaigns.

The COVID alert app is based on the Google-Apple exposure notification API (GAEN API), a functionality that the tech companies rolled out in April 2020. The Canadian government built an app around the GAEN API, which became the COVID alert app, and managed the system for uploading positive cases.