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Black patients tend to have better health outcomes when cared for by Black physicians, yet Black doctors make up only 5% of U.S. physicians, despite Black people comprising 14% of the population. This analysis of data from Florida medical schools showed a higher enrollment of Black first-year students (13.5%) compared to the national average (9%), and a national increase from 6% in 2013 to 9% in 2021, aligning with the rise of social justice movements. Increasing Black medical student enrollment could reduce health disparities and improve outcomes for Black communities.

Powered by the sociological framework that exposure to television bleeds into social biases, limiting media representation of women and minority groups may lead to real-world implications and manifestations of racial and gender disparities. To address this phenomenon, the researchers in this article take a look at primetime fictional representation of minorities and women as lawyers and physicians and compare television representation to census data of the same groups within real-world legal and medical occupations. The authors maintain the hypothesis that representation of female and minority groups as television lawyers and doctors is lower than that of their white male counterparts relative to population demographics - a trend that they expect to also be reflected in actual practice. With fictional racial and gender inequalities and corresponding real-world trends highlighted within this article, the researchers call for address towards representation biases that reinforce each other in both fictional and non-fictional spheres.

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.

Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.

Bacterial infection is resurging as one of the most dangerous challenges facing the medical establishment. Americans spend about 55 to 70 billion dollars per year on antibiotics, yet these antibiotics are becoming increasingly ineffective as illness-causing bacteria gain resistance to the prescribed drugs. We tested if 11 commonly-used spices could inhibit growth of the gram-negative bacteria, E. coli, the main takeaway from these experiments is that certain spices and herbs have antibacterial effects that inhibit growth of E.coli , and these spices could show similarly promising activity towards other bacteria.

Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.

Cell-free biologicals are a novel method of treating clinical conditions which involve chronic inflammation such as tendonitis and osteoarthritis. This study compared platelet-derived growth factor (PDGF) and vascular endothelial growth factor (VEGF) in platelet-rich plasma (PRP), activated PRP (aPRP), and platelet lysate (PL). It was hypothesized that PL would contain higher concentrations of growth factors than PRP and that different storage temperatures for PL would diminish cytokine expression. Results demonstrated PL had the highest concentrations of both cytokines, with concentrations slightly diminishing at-80C. aPRP and PRP demonstrated lower concentrations of PDGF and VEGF than PL.

Major Depressive Disorder (MDD), and Post-Traumatic Stress Disorder (PTSD) are two of the fastest growing comorbid diseases in the world. Using publicly available datasets from the National Institute for Biotechnology Information (NCBI), Ravi and Lee conducted a differential gene expression analysis using 184 blood samples from either control individuals or individuals with comorbid MDD and PTSD. As a result, the authors identified 253 highly differentially-expressed genes, with enrichment for proteins in the gene ontology group 'Ribosomal Pathway'. These genes may be used as blood-based biomarkers for susceptibility to MDD or PTSD, and to tailor treatments within a personalized medicine regime.

The authors surveyed individuals diagnosed with coronary artery disease about their mental health to study a potential connection between coronary artery disease and depression.

Here, based on the identified importance of physical activity in the development of young children, the authors investigated the effects of socioeconomic factors on the amount of physical activity of government-school children in India. They found significant differences between boys and girls, rural and urban, and children who were encouraged to exercise and those who were not. Overall, they suggest that their findings point to the important role of schools and communities in promoting healthy active lifestyles for developing children.