Latest AI and machine learning research in transplantation for healthcare professionals.
Medical image segmentation using deep learning (DL) has enabled the development of automated analysis pipelines for large-scale population studies. However, state-of-the-art DL methods are prone to hallucinations, which can result in anatomically implausible segmentations. With manual correction impractical at scale, automated quality control (QC) techniques have to address the challenge. While pr...
Accurate and timely mortality prediction is essential for nursing clinical decision-making in intensive care units (ICUs). Although the Sequential Organ Failure Assessment (SOFA) score is widely used to evaluate organ dysfunction, its manual calculation limits routine application in fast-paced clinical environments. This study aimed to enhance ICU system-level safety and workflow efficiency by ref...
BACKGROUND: Accurate inpatient census forecasting is important for cell therapy and blood and marrow transplantation (BMT) programs because bed capaci...
Neoadjuvant chemoradiotherapy (nCRT) is standard for locally advanced rectal cancer but increases postoperative complication (POC) risks due to tissue...
OBJECTIVE: Acupuncture prescriptions involve complex compatibility mechanisms grounded in multi-symptom and multi-acupoint interactions, embodying mil...
Rare diseases are often critically underfunded, leaving many patients without timely diagnosis and treatment. In this News and Perspectives article, J...
Electrolyte discovery for rechargeable batteries today relies on heuristic trial-and-error or high-throughput screening of existing molecules. Here, w...
The therapeutic landscape of colorectal cancer (CRC) has evolved with the identification of molecular subtypes, including mismatch repair-deficient/mi...
Perfluorooctanoic acid (PFOA), a persistent environmental pollutant, represents a chronic environmental stressor, yet its role in osteosarcoma progres...
PURPOSE: Given the existing uncertainties regarding the link between Di(2-ethylhexyl) phthalate (DEHP) exposure and gastric cancer (GC) progression, t...
OBJECTIVE: The successful integration of Machine Learning (ML) models into clinical practice remains limited, as they often lack the standardized, qua...
Kidney transplantation is the preferred treatment for end-stage renal disease, yet donor scarcity and inefficiencies in allocation systems create majo...
Liver ischemia-reperfusion injury (LIRI), a significant complication following liver transplantation and surgical procedures, remains inadequately add...
Accurate prediction of molecular properties is essential for accelerating drug discovery, yet current deep learning methods generally lack reliable un...
BACKGROUND: Artificial intelligence (AI) enabled systems hold significant promise for transforming health care delivery. These technologies are freque...
Despite remarkable advances in transplant pathology, molecular diagnostics, imaging, and biomarker discovery, uncertainty remains an intrinsic feature...
RATIONALE & OBJECTIVE: Despite advantages in survival and quality of life with kidney transplantation (KT) compared to other treatments for kidney fai...
Psychiatric, neurodevelopmental, and neurodegenerative disorders, including Alzheimer's disease (AD), attention-deficit/hyperactivity disorder (ADHD),...
Accurate organ weight determination is essential in forensic autopsy. Postmortem computed tomography (CT) combined with Artificial Intelligence (AI)-b...
BACKGROUND: Fast risk stratification is essential for patients with sepsis, a life-threatening condition associated with high mortality, as it guides ...