This review explores how multi-source data-driven machine learning is transforming lung cancer care, from early screening and diagnosis to personalized treatment and prognosis. It examines imaging, multi-omics, liquid biopsy, pathology, and clinical data, alongside traditional and advanced machine learning approaches. By linking data characteristics with model selection and clinical applications, the review highlights opportunities for precision medicine while addressing challenges in data standardization, multimodal integration, interpretability, and effective clinical translation.

Worcester Polytechnic Institute researcher Catherine Whittington is launching a new project to develop laboratory models for the study of uterine fibroids, and before work had even begun, WPI students had already played a critical role.

UC San Diego has launched Brain-FRAMe, an innovative program integrating neuroscience and immunology to improve brain health and clinical care for people living with HIV and methamphetamine use disorder.

A new review from Hasanuddin University highlights how chitosan and alginate-based composite beads could be the next-generation solution for sustainable wastewater remediation. By combining naturally derived biopolymers with functional additives, these composite beads demonstrate improved adsorption capacity, mechanical stability, reusability, and stronger pollutant binding. The review outlines a roadmap for advancing such composites into stimuli-responsive smart materials and extending their applications beyond water treatment to circular bioeconomy, smart agriculture, and even precision medicine.