In this study, we examined the utility of using machine learning (ML) to predict venous thromboembolism (VTE) in cancer patients. It allowed us to draw insight into our feature pool and identify the features that could have the most utility in the context of developing an efficient ML classifier. Our ML-based prediction model achieved an area under the receiver operating characteristic curve of 0.778 ± 0.006 when trained on a set of 15 features. Our result surpasses the most validated clinical scoring system for VTE risk assessment in cancer patients by 16.1%. We additionally found cancer stage information to be a useful predictor after all performed feature selection processes despite not being used in existing score-based approaches.

An overall healthy lifestyle (including healthy diet, noncurrent smoking, noncurrent drinking, regular exercise, normal body mass index (BMI), adequate sleep duration, and limited sedentary behavior) was significantly associated with lower odds of cardiometabolic diseases. Among specific lifestyle factors, normal BMI, noncurrent drinking, and limited sedentary behavior were the major contributors to the observed associations.

This study investigated the factors on burnout of village physicians in China, particularly exploring the effects of the medical alliance. Fewer working years, too much farming work and less workload of medical services were significantly related to exacerbation of burnout. While more supports from higher-level facilities, including transmission of images and testing results across facilities and tele-consultations, were conducive to burnout alleviation.

This study investigates the impact of COVID-19 on healthcare workers in Malawi through a hermeneutic phenomenological approach. Findings reveal the struggles and needs of healthcare workers in a low-income nation, and highlight the role of personal biases and fear. The study provides directions for future policies and strategies to better prepare for disease outbreaks.

The advancement of large language models (LLMs) promises to bring significant changes in health care, with extensive applications spanning pre-consultation, diagnostic, and management phases. Moreover, LLMs hold potential utility in medical education and medical writing. Concurrently, it is imperative to recognize the limitations of LLMs, strengthen review measures and enhance supervision system, thereby facilitating more effective collaboration between related personnel and LLMs.

Coronavirus disease-2019 pandemic has spread across 200+ countries in a very short time span. Many have died and many are getting infected daily. But the rate has slowed down now. Improved pharmacotherapeutics and immunization with precautionary protocols have diminished its impact across the globe. The work focuses on highlighting the disease epidemiology and its socioeconomic, geopolitical, and health impact from 2019 to 2023. (Graphical abstract is created with BioRender.com)