Deciphering the building blocks of life has long been a painstaking process, but now a quiet revolution in computing power is changing everything – with research at the University of Otago’s Faculty ...
Depression is one of the most widespread mental health disorders worldwide, affecting approximately 4% of the global ...
Dr Michele Orini shares how machine learning can help identify critical VT ablation targets for a safer, data-driven ...
A new machine-learning-based approach to mapping real-time tumor metabolism in brain cancer patients, developed at the ...
With climate change posing an unprecedented global challenge, the demand for environmentally friendly solvents in green chemical processes and carbon dioxide capture has surged. Ionic liquids (ILs) ...
Abstract: The prediction and modeling of ionospheric total electron content (TEC) have consistently been a focal point for researchers, as it holds significant implications for satellite positioning, ...
AI is the broad goal of creating intelligent systems, no matter what technique is used. In comparison, Machine Learning is a specific technique to train intelligent systems by teaching models to learn ...
Background: The disease burden of acute myeloid leukemia (AML) continues to pose a significant public health challenge globally. Mitochondria play a critical role in tumor development and progression ...
The drug development pipeline is a costly and lengthy process. Identifying high-quality "hit" compounds-those with high potency, selectivity, and favorable metabolic properties-at the earliest stages ...
A rotating cylinder with its side cut away to expose the core, showing patches of purple, blue, green, yellow, and orange that are dense in the middle and more diffuse toward the edges. This rotating ...
A powerful new AI predicts how over 1,000 diseases may unfold across a person’s life, opening doors for precision prevention, policy planning, and bias-aware healthcare innovation. Study: Learning the ...
The Asian Development Bank, in collaboration with Cornell University, has released a groundbreaking study that examines both the promise and the pitfalls of using machine learning for poverty mapping.
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