Latest AI and machine learning research in surveys for healthcare professionals.
Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predict surgical outcomes. However, the large quantity of data required and lack of model interpretability represent substantial barriers to the validity and reproducibility of DL models. The objective of this study was to systematically review the characteristics of DL studies involving neurosurgical ou...
The application of machine-learning technologies to medical practice promises to enhance the capabilities of healthcare professionals in the assessment, diagnosis, and treatment, of medical conditions. However, there is growing concern that algorithmic bias may perpetuate or exacerbate existing health inequalities. Hence, it matters that we make precise the different respects in which algorithmic ...
Robot-assisted laparoscopic partial nephrectomy (RAPN) for completely endophytic renal tumors is challenging because of the tumor complexity. The enu...
The Self-Rating Depression Scale (SDS) questionnaire is commonly utilized for effective depression preliminary screening. The uncontrolled self-admini...
Neuropsychiatric disorders such as schizophrenia are very heterogeneous in nature and typically diagnosed using self-reported symptoms. This makes it ...
Computer-coded verbal autopsy (CCVA) algorithms predict cause of death from high-dimensional family questionnaire data (verbal autopsy) of a deceased ...
Proteins interact with each other to play critical roles in many biological processes in cells. Although promising, laboratory experiments usually suf...
Automated analysis and quantification of physiological signals in clinical practice and medical research can reduce manual labor, increase efficiency,...
General practitioners (GPs) are playing a key role in skin cancer screening. Non-melanoma skin cancer is frequent and difficult to diagnose. We aimed ...
PURPOSE: Developing medical students' clinical reasoning requires a structured longitudinal curriculum with frequent targeted assessment and feedback....
Cell biology is fundamentally limited in its ability to collect complete data on cellular phenotypes and the wide range of responses to perturbation. ...
Tea can help to regulate the mood of human. Based on the influence of tea on people's mood and attention, this study explored the tea concentration wh...
Artificial intelligence (AI) will likely affect various fields of medicine. This article aims to explain the fundamental principles of clinical valida...
The COVID-19 pandemic is presenting a disproportionate impact on minorities in terms of infection rate, hospitalizations, and mortality. Many believe ...
The development of neuroimaging instrumentation has boosted neuroscience researches. Consequently, both the fineness and the cost of data acquisition ...
Datasets sourced from people with disabilities and older adults play an important role in innovation, benchmarking, and mitigating bias for both assis...
Accumulating evidence demonstrates the impact of bias that reflects social inequality on the performance of machine learning (ML) models in health car...
Large classes taught with didactic lectures and assessed with multiple-choice tests are commonly reported to promote lower order (LO) thinking and a s...
Precision medicine (MP), using machine learning (ML) techniques of artificial intelligence (AI), analyzes the so-called "big data" to improve diagnost...
Diagnostic processes typically rely on traditional and laborious methods, that are prone to human error, resulting in frequent misdiagnosis of disease...