A groundbreaking study led by USC Assistant Professor of Computer Science Ruishan Liu has uncovered how specific genetic mutations influence cancer treatment outcomes-insights that could help doctors ...
Machine learning can enhance ARF outcome predictions but faces challenges like data quality, system heterogeneity, and clinician acceptance. High ARF mortality and mechanical ventilation risks ...
A machine learning model can use patient-reported data and remote therapeutic monitoring to accurately assess low disease ...
New research presented during the 2024 San Antonio Breast Cancer Symposium (SABCS) reveals a new machine learning model that could change the way metastatic breast cancer is treated in the future. By ...
A total of 590 patients were identified, 432 in the development set and 158 in the validation set. The median age was 51 years, and 55.8% (329 of 590) experienced grade 3 or 4 toxicity. The ...
Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...
Please provide your email address to receive an email when new articles are posted on . Machine learning models can predict which patients receiving lung cancer therapy may need urgent care visits.
Nearly 85% of the 1.7 million adolescents with HIV live in sub-Saharan Africa, along with half of the nearly 40 million people in the world living with HIV. Although the government in Uganda provides ...
New data provide key mechanistic insights into how TG4050 induces and sustains potent, CD8+ T cell responses in operable HNSCC[*] ...
Some results have been hidden because they may be inaccessible to you
Show inaccessible results
Feedback