Medicine is rapidly evolving from statistical, evidence-based approaches to predictive, genotype-directed care, driven by ...

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve researchers' ability to detect complex genetic alterations in cancer genomes.

Discover how AI healthcare technology and machine learning diagnosis are transforming disease detection, improving accuracy, and reshaping patient care in today’s evolving medical landscape. Pixabay, ...

A new algorithm could drive breakthroughs in understanding cancer, Alzheimer's disease and other potentially fatal conditions ...

Endovascular aortoiliac revascularization is a common treatment option for peripheral artery disease that carries non-negligible risks. Outcome prediction tools may support clinical decision-making ...

A team of researchers at the Icahn School of Medicine at Mount Sinai has developed a new method to identify and reduce biases in datasets used to train machine-learning algorithms—addressing a ...

This study aimed to explore the combined impacts of occupational noise and dust on hearing and extra-auditory functions and identify associated risk factors via machine learning techniques. Data from ...

Rapid advances in artificial intelligence (AI), computational medicine, and digital health are fundamentally reshaping respiratory and critical care ...

Smartwatches are among the wearable devices that gather health data. Translating that data into useful information can be complicated and expensive. (iStock) The human body constantly generates a ...

From wearables for health monitoring and self-care apps, to machine learning analysis of medical images, the potential of digital technologies to revolutionise healthcare has commanded many headlines.

Machine learning components are enabling advances in self-driving cars, the power grid, and robotic medicine, but what are the implications for safety? Decades of research and practice in safety ...