Machine learning can accurately predict pre-admission baseline hemoglobin and creatinine in intensive care patients.

Patients admitted to the intensive care unit frequently have anemia and impaired renal function, but often lack historical blood results to contextualize the acuteness of these findings. Using data available within two hours of ICU admission, we developed machine learning models that accurately (AUC 0.86-0.

Artificial intelligence and machine learning in clinical development: a translational perspective.

Future of clinical development is on the verge of a major transformation due to convergence of large new digital data sources, computing power to identify clinically meaningful patterns in the data using efficient artificial intelligence and machine-learning algorithms, and regulators embracing this change through new collaborations. This perspective summarizes insights, recent developments, and recommendations for infusing actionable computational evidence into clinical development and health care from academy, biotechnology industry, nonprofit foundations, regulators, and technology corporations. Analysis and learning from publically available biomedical and clinical trial data sets, real-world evidence from sensors, and health records by machine-learning architectures are discussed.

Poisson traces, D-modules, and symplectic resolutions.

We survey the theory of Poisson traces (or zeroth Poisson homology) developed by the authors in a series of recent papers. The goal is to understand this subtle invariant of (singular) Poisson varieties, conditions for it to be finite-dimensional, its relationship to the geometry and topology of symplectic resolutions, and its applications to quantizations. The main technique is the study of a canonical D-module on the variety.

Nanoporous membrane device for ultra high heat flux thermal management.

High power density electronics are severely limited by current thermal management solutions which are unable to dissipate the necessary heat flux while maintaining safe junction temperatures for reliable operation. We designed, fabricated, and experimentally characterized a microfluidic device for ultra-high heat flux dissipation using evaporation from a nanoporous silicon membrane. With ~100 nm diameter pores, the membrane can generate high capillary pressure even with low surface tension fluids such as pentane and R245fa.

Researching for better instructional methods using AB experiments in MOOCs: results and challenges.

We conducted two AB experiments (treatment vs. control) in a massive open online course. The first experiment evaluates deliberate practice activities (DPAs) for developing problem solving expertise as measured by traditional physics problems.