Do no harm: a roadmap for responsible machine learning for health care

Interest in machine-learning applications within medicine has been growing, but few studies have progressed to deployment in patient care. We present a framework, context and ultimately guidelines for accelerating the translation of machine-learning-based interventions in health care. To be successful, translation will require a team of engaged stakeholders and a systematic process from beginning (problem

Read More

Distinguishing different subtypes of sepsis by machine learning sets the stage for individualized treatment, researchers say

Four clinical sepsis phenotypes were identified that correlated with host-response patterns and clinical outcomes, researchers reported here. The four novel sepsis phenotypes — alpha (α), beta (β), gamma (γ), and delta (δ) — with different demographics, laboratory values, and patterns of organ dysfunction were derived, validated, and shown to correlate with biomarkers and mortality, according

Read More

Machine learning in medicine

The field of medicine has so far relied heavily on heuristic approaches, whereby knowledge is acquired through experience and self-learning, which is imperative in the highly variable healthcare environment. The increase in knowledge and understanding of diseases has been associated with the growth in information and data partly thanks to advances in tools that generate

Read More