New ML models demonstrate high accuracy in predicting lymph node metastasis in prostate cancer. A meta-analysis of 31 studies reveals promising results for improved diagnosis and treatment.
The UK gov is investing £21m to bring AI imaging and decision-support tools to NHS to improve diagnosis & treatment of heart conditions, cancer, and strokes, and to aid in early detection of lung cancer. NHS trusts can apply for funds for any appropriate AI diagnostic tool. #AIforNHS
UC Riverside researchers use machine learning to uncover personalized COVID-19 treatment regimens. The study discovered the most effective drug combinations, as well as the influence of patient factors on treatment effectiveness. The research highlights the potential of machine learning in healthcare and the importance of ongoing COVID-19 research.
This article discusses the use of machine learning (ML) algorithms to diagnose and treat atopic dermatitis (AD). Research conducted at Third Xiangya Hospital in Central South University has revealed that these ML models are highly accurate for distinguishing between AD lesions and non-lesions. Additionally, the results of this study have shown a positive correlation between the ML scores and SCORAD (Scoring Atopic Dermatitis) in patients treated with biological therapy. Although there is more data needed for better validation and model stability, this research suggests the potential for ML-based models in clinical AD diagnosis and treatment efficacy.
This article discusses the results of a recent study that analyzed the proficiency of Open AI's ChatGPT in comparison to that of healthcare professionals. The study revealed that the chatbot gave more precise, personalized answers with higher compassionate levels than those provided by medical doctors. Research outcomes show that the chatbot's response was 3.6 times better in quality and 9.8 times higher in empathy when compared to that of medical professionals.
Explore the evolution of tech policy from Obama's optimism to Harris's vision at the Democratic National Convention. What's next for Democrats in tech?