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Multimodal deep learning improving the accuracy of pathological diagnoses for membranous nephropathy.
Renal failure
Jul 14, 2025
OBJECTIVES: Renal biopsy is the gold standard for the diagnosis of glomerular diseases including membranous nephropathy (MN), however, it faces challenges in accuracy, objectivity, and reproducibility of tissue evaluation. This study aims to develop ...
A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study.
World journal of emergency surgery : WJES
Jul 14, 2025
BACKGROUND: Accurately identifying difficult laparoscopic cholecystectomy (DLC) preoperatively remains a clinical challenge. Previous studies utilizing clinical variables or morphological imaging markers have demonstrated suboptimal predictive perfor...
Characterizing individual and methodological risk factors for survey non-completion using machine learning: findings from the U.S. Millennium Cohort Study.
BMC medical research methodology
Jul 14, 2025
BACKGROUND: Missing survey data can threaten the validity and generalizability of findings from longitudinal cohort studies. Respondent characteristics and survey attributes may contribute to patterns of survey non-completion, a form of missing data ...
Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model.
BMC cancer
Jul 14, 2025
BACKGROUND: Accurately distinguishing the different molecular subtypes of 2021 World Health Organization (WHO) grade 4 Central Nervous System (CNS) gliomas is highly relevant for prognostic stratification and personalized treatment.
Immunodiagnostic plasma amino acid residue biomarkers detect cancer early and predict treatment response.
Nature communications
Jul 14, 2025
The immune response to tumour development is frequently targeted with therapeutics but remains largely unexplored in diagnostics, despite being stronger for early-stage tumours. We present an immunodiagnostic platform to detect this. We identify a pa...
The Helicobacter pylori AI-clinician harnesses artificial intelligence to personalise H. pylori treatment recommendations.
Nature communications
Jul 14, 2025
Helicobacter pylori (H. pylori) is the most common carcinogenic pathogen globally and the leading cause of gastric cancer. Here, we develop a reinforcement learning-based AI Clinician system to personalise treatment selection and evaluate its ability...
Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms.
PloS one
Jul 14, 2025
Automated detection of emotional states through brain-computer interfaces (BCIs) offers significant potential for enhancing user experiences and personalizing services across domains such as mental health, adaptive learning and interactive entertainm...
Lay beliefs about AI assessment of interpersonal skills in personnel selection.
Scientific reports
Jul 13, 2025
Artificial intelligence (AI) is revolutionizing talent acquisition, with organizations increasingly replacing humans with AI technologies in personnel selection processes. Field studies of nurses provide preliminary evidence that AI can outperform hu...
Development and validation of a machine learning-based nomogram for survival prediction of patients with hilar cholangiocarcinoma after curative-intent resection.
Scientific reports
Jul 12, 2025
Hilar cholangiocarcinoma (hCCA), a rare cancer of the biliary system, has a poor prognosis. This study aimed to investigate the risk factors affecting the survival of patients with hCCA after curative-intent resection and establish a survival predict...
Detecting schizophrenia, bipolar disorder, psychosis vulnerability and major depressive disorder from 5 minutes of online-collected speech.
Translational psychiatry
Jul 12, 2025
Psychosis poses substantial social and healthcare burdens. The analysis of speech is a promising approach for the diagnosis and monitoring of psychosis, capturing symptoms like thought disorder and flattened affect. Recent advancements in Natural Lan...
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