Latest AI and machine learning research in clinical trials for healthcare professionals.
BACKGROUND AND OBJECTIVES: Delays in septic shock diagnosis cause preventable mortality in children. Evidence is limited around early recognition strategies. The hypothesis was that clinical decision support (CDS) based on machine-learning predictive models would increase the proportion of children receiving septic shock treatment prior to shock onset.
This study targets an important question in the synthesis of graphitic carbon nitride (g-CN) nanosheets via liquid-phase exfoliation (LPE): how does a binary solvent mixture perform relative to its components? A machine learning model based on Extra Trees Regressor, when applied to 171 pure solvents and 14,535 binary solvents resulting from their arbitrary combination, reveals an interesting pheno...
Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality globally, with increasing incidence rates, particularly in early-...
Plastic surgery, by nature an innovative discipline, has historically relied on clinical case reports to advance its techniques. Often unique, these c...
Left-turn slip lanes, also known as channelised right-turn lanes in right-hand driving countries, are widely implemented to facilitate left-turning at...
Starting in the 1970s with robots that were physically isolated from contact with their human co-workers, robots now collaborate with human workers to...
Anesthesiology has a longstanding commitment to patient safety, characterized by innovative research, quality improvement, multidisciplinary collabora...
The use of Natural Language Processing (NLP) in highstakes AI-based applications has increased significantly in recent years, especially since the e...
Autonomous Driving Systems (ADSs) continue to face safety-critical risks due to the inherent limitations in their design and performance capabilitie...
Autonomous drifting is a complex and crucial maneuver for safety-critical scenarios like slippery roads and emergency collision avoidance, requiring...
Given the growing influence of language model-based agents on high-stakes societal decisions, from public policy to healthcare, ensuring their benef...
Surgical risk identification is critical for patient safety and reducing preventable medical errors. While multimodal large language models (MLLMs) ...
Lifting on construction sites, as a frequent operation, works still with safety risks, especially for modular integrated construction (MiC) lifting ...
We introduce fast randomized algorithms for solving semidefinite programming (SDP) relaxations of the partial permutation synchronization (PPS) prob...
Recent advances in LLMs have greatly improved general-domain NLP tasks. Yet, their adoption in critical domains, such as clinical trial recruitment,...
The integration of AI/ML into medical devices is rapidly transforming healthcare by enhancing diagnostic and treatment facilities. However, this adv...
Surgical training integrates several years of didactic learning, simulation, mentorship, and hands-on experience. Challenges include stress, technic...
RNA interference (RNAi) has emerged as a transformative approach for cancer therapy, enabling precise gene silencing through small interfering RNA (si...
Policymakers in resource-constrained settings require experimental designs that satisfy strict budget limits while ensuring precise estimation of tr...
Optical coherence tomography (OCT) has sufficient depth penetration for detection of skin pathologies, but its detection effectiveness can be aided by...