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Diabetes is a growing health concern in the developing world. This study aimed to develop a questionnaire that uses factors including age, blood pressure, BMI, and family history to predict whether Filipino participants are at risk for diabetes.

The authors identify disinfectant-resistant bacterial strains of infection-causing bacteria from samples collected at a hospital setting.

The authors studied the impact of drying blood as a storage solution for space travel.

The authors looked at if there was any correlation between the phase of the moon and admissions for psychiatric concerns.

This study follows the process of single-cloning and the growth of a homogeneous cell population in a superficial environment over the course of six weeks with the end goal of showing which of five tumor growth models commonly used to predict heterogeneous cancer cell population growth (Exponential, Logistic, Gompertz, Linear, and Bertalanffy) would also best exemplify that of homogeneous cell populations.

The authors looked at different factors, such as age, pre-existing conditions, and geographic region, and their ability to predict what an individual's health insurance premium would be.

The authors looked at different models of semantic segmentation to determine which may be best used in the future for segmentation of CT scans to help diagnose certain conditions.

As AI becomes more integrated into healthcare, public trust in AI-developed treatment plans remains a concern, especially for emotionally charged health decisions. In a study of 81 community college students, AI-created treatment plans received lower trust ratings compared to physician-developed plans, supporting the hypothesis. The study found no significant differences in AI trust levels across demographic factors, suggesting overall skepticism toward AI-driven healthcare.

The authors test different machine learning algorithms to remove background noise from audio to help people with hearing loss differentiate between important sounds and distracting noise.

While serving as an immediate address for psychological safety and stability, psychological first aid (PFA) currently lacks the incorporation of triage. Without triage, patients cannot be prioritized in correspondence to condition severity that is often called for within emergency conditions. To disentangle the relevance of a potential triage system to PFA, the authors of this paper have developed a method to quantify resilience - a prominent predictor of the capability to recover from a disaster. With this resilience index, they have quantified resilience of differing age, race, and sex demographics to better inform the practice of PFA and potential demographic prioritization via a triage system.