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Automated Quantification of Cerebral Microbleeds in SWI: Association with Vascular Risk Factors, White Matter Hyperintensity Burden, and Cognitive Function.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: The amount and distribution of cerebral microbleeds (CMB) are important risk factors for cognitive impairment. Our objective was to train and validate a deep learning (DL)-based segmentation model for cerebral microbleeds (CMB...

Deep learning model for predicting the RAS oncogene status in colorectal cancer liver metastases.

Journal of cancer research and therapeutics
BACKGROUND: To develop a deep learning radiomics (DLR) model based on contrast-enhanced computed tomography (CECT) to assess the rat sarcoma (RAS) oncogene status and predict targeted therapy response in colorectal cancer liver metastases (CRLM).

Artificial intelligence for early detection of lung cancer in GPs' clinical notes: a retrospective observational cohort study.

The British journal of general practice : the journal of the Royal College of General Practitioners
BACKGROUND: The journey of >80% of patients diagnosed with lung cancer starts in general practice. About 75% of patients are diagnosed when it is at an advanced stage (3 or 4), leading to >80% mortality within 1 year at present. The long-term data in...

High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural Networks.

IEEE transactions on medical imaging
The functional analysis of the left atrium (LA) is important for evaluating cardiac health and understanding diseases like atrial fibrillation. Cine MRI is ideally placed for the detailed 3D characterization of LA motion and deformation but is lackin...

Modality-Aware Discriminative Fusion Network for Integrated Analysis of Brain Imaging Genomics.

IEEE transactions on neural networks and learning systems
Mild cognitive impairment (MCI) represents an early stage of Alzheimer's disease (AD), characterized by subtle clinical symptoms that pose challenges for accurate diagnosis. The quest for the identification of MCI individuals has highlighted the impo...

Artificial intelligence model for the assessment of unstained live sperm morphology.

Reproduction & fertility
ABSTRACT: Traditional sperm morphology assessment requires staining and high magnification (100×), rendering sperm unsuitable for further use. We aimed to determine whether an in-house artificial intelligence (AI) model could reliably assess normal s...

Machine Learning Multimodal Model for Delirium Risk Stratification.

JAMA network open
IMPORTANCE: Automating the identification of risk for developing hospital delirium with models that use machine learning (ML) could facilitate more rapid prevention, identification, and treatment of delirium. However, there are very few reports on th...

Real-Time AI-Assisted Insulin Titration System for Glucose Control in Patients With Type 2 Diabetes: A Randomized Clinical Trial.

JAMA network open
IMPORTANCE: Type 2 diabetes (T2D) is one of the most prevalent chronic diseases in the world. Insulin titration for glycemic control in T2D is crucial but limited by the lack of personalized and real-time tools.

Predicting Agitation Events in the Emergency Department Through Artificial Intelligence.

JAMA network open
IMPORTANCE: Agitation events are increasing in emergency departments (EDs), exacerbating safety risks for patients and clinicians. A wide range of clinical etiologies and behavioral patterns in the emergency setting make agitation prediction difficul...

Evaluation of an Ambient Artificial Intelligence Documentation Platform for Clinicians.

JAMA network open
IMPORTANCE: The increase of electronic health record (EHR) work negatively impacts clinician well-being. One potential solution is incorporating an ambient artificial intelligence (AI) documentation platform.