Latest AI and machine learning research in clinical trials for healthcare professionals.
OBJECTIVE: Machine learning (ML) models are increasingly used to generate electrical stimulation patterns in neuroprosthetic devices such as visual prostheses. While these models promise precise and personalized control, they also introduce new safety risks when model outputs are delivered directly to neural tissue. We propose a systematic, quantitative approach to detect and characterize unsafe s...
Surrogate markers are most commonly studied within the context of randomized clinical trials. However, the need for alternative outcomes also extends to real-world public health and social science research, where randomized trials are often impractical. While standard methods for evaluating surrogate markers largely rely on the assumption of randomized treatment, there is a significant gap in appl...
Laryngeal cancer is a common head-and-neck malignant tumor with geographically variable incidence. Its lack of specific early clinical symptoms often ...
BACKGROUND: Subacute low back pain (LBP) is a highly prevalent condition and a major contributor to disability and health care burden. Early identific...
BACKGROUND: While medications are essential for preventing and treating disease, they can also cause harm. Evidence synthesis has been widely adopted ...
PURPOSE: Oligometastatic prostate cancer (oligoPCa) represents a clinical state of limited metastatic spread in which metastasis-directed therapy (MDT...
BACKGROUND AND OBJECTIVE: Neuroimaging AI systems increasingly influence clinical decisions, yet demographic exclusions in training datasets may compr...
Probiotic therapeutics are evolving from generalized wellness supplements to precision Live Biotherapeutic Products aimed at specific disease targets....
RATIONALE AND OBJECTIVES: This study aims to evaluate whether radiomics methods used on breast mammography (MG) and ultrasound (US) could distinguish ...
BACKGROUND: Chronic inflammation in older adults is a key contributor to functional decline and mortality. Although anti-inflammatory medications have...
The clinical adoption of artificial intelligence (AI) has focused on enabling automation, but conventional accuracy metrics fail to answer a key quest...
BACKGROUND: The integration of artificial intelligence in healthcare has transformed clinical practice and research methodologies. However, concerns r...
BACKGROUND: Clinicians spend over 30% of their workday on electronic health records, reducing patient interaction and contributing to burnout. Preanes...
INTRODUCTION: Active post-vaccination surveillance is vital for ensuring vaccine safety, particularly in monitoring Adverse Events of Special Interest...
INTRODUCTION: Depression frequently co-occurs with psychosis and is associated with poor outcomes. Early identification of patients at risk of persist...
BACKGROUND: The aging trend of people living with HIV or AIDS in China is increasing day by day. Frailty is a common condition among older adults livi...
The widespread adoption of virtual residency interviews in response to the COVID-19 pandemic led to an explosion in literature comparing the pros and ...
Neurofeedback therapy (NFT) has emerged as a promising noninvasive intervention for autism spectrum disorder (ASD), targeting core symptoms such as so...
OBJECTIVES: Despite the rapid growth of generative artificial intelligence (AI), virtually no research exists examining the psychological impacts of v...
Current methods for radiological classification in traumatic brain injury (TBI), such as the Marshall and Rotterdam score, provide an incomplete descr...