Care of terminally ill / Palliative care

Perceived Potential and Challenges of Supporting Coronary Artery Disease Treatment Decisions With AI: Qualitative Study.

BACKGROUND: Coronary revascularization decision-making for patients with coronary artery disease (CAD) can be complex and challenging. Artificial intelligence (AI) has the potential to improve this decision-making by bringing data-driven insights to the point of care. OBJECTIVE: We aimed to elicit, collect, and analyze various stakeholders' perceived potential and challenges related to developing,...

Interpretable Machine Learning Model Using Digitized US Features for Classifying Complex Thyroid Nodules.

Purpose To develop a digitized integrated feature-based interpretable machine learning classification model to accurately recognize complex thyroid nodules while efficiently diagnosing conventional thyroid nodules (thyroid nodules with typical benign or malignant ultrasound features). Materials and Methods Thyroid ultrasound images with pathologically confirmed nodules were retrospectively collect...

Risk stratification in diabetic kidney disease: a review of prediction models for methodological advances and clinical application.

BACKGROUND: Diabetic kidney disease (DKD) represents the leading cause of end-stage renal disease (ESRD) worldwide, characterized by a complex pathoph...

Full-Scope Vectorization of Geographical Elements from Large-Size Remote Sensing Imagery.

Large-size very-high-resolution (VHR) remote sensing imagery has emerged as a critical data source for high-precision vector mapping of multi-scale ge...

Developing a Multimodal Screening Algorithm for Mild Cognitive Impairment and Early Dementia in Home Health Care: Protocol for a Cross-Sectional Case-Control Study Using Speech Analysis, Large Language Models, and Electronic Health Records.

BACKGROUND: Mild cognitive impairment and early dementia (MCI-ED) are frequently unrecognized in routine care, particularly in home health care (HHC),...

A Deep Learning-Based Human-Robot Collaborative Navigation Framework for Vascular Interventional Surgery.

BACKGROUND: Autonomous robotic surgery has demonstrated its potential for the optimal outcomes. However, vascular interventional surgery (VIS) with fl...

Interpretable model-driven end-to-end deep learning of geometric shaping for DML-based IM/DD systems.

Direct modulation lasers (DMLs) are a low-cost technology for short-reach intensity modulation and direct detection (IM/DD) systems due to their small...

Machine Learning Based Prediction of Tibial Insert Thickness in Total Knee Arthroplasty From Intraoperative Knee Joint Laxity Data.

Total knee arthroplasty (TKA) represents the gold standard for relieving pain and restoring function in patients with end-stage knee osteoarthritis. S...

SLPM: a lightweight deep learning model for end-to-end paper ECG digitization.

OBJECTIVE: The digitization of paper electrocardiograms (ECGs) faces several challenges, including amplified errors during segmentation and signal ext...

Mapping at-risk transportation infrastructure assets using statistical and machine learning methods.

Geotechnical assets such as highway embankments and slopes (HWS) are critical to the integrity of transportation infrastructure. However, they are lar...

DMPFDet: An end-to-end deformable mutual-promotion learning network for multispectral visible-infrared fusion detection.

Multimodal image fusion and object detection significantly enhance detection accuracy and robustness in complex environments, which is crucial for aut...

Radiomics analysis of early pregnancy ultrasound images to predict viability at the end of first trimester.

To determine whether there are radiomic ultrasound features of early pregnancy when viability is unknown, which in combination with clinical features,...

IUGC: A benchmark of landmark detection in end-to-end intrapartum ultrasound biometry.

Accurate intrapartum biometry plays a crucial role in monitoring labor progression and preventing complications. However, its clinical application is ...

LMSA-net: a lightweight multi-scale attention network for eeg-based emotion recognition.

Electroencephalogram (EEG)-based emotion recognition holds great potential in affective computing, mental health assessment, and human-computer intera...

A Framework for Healthcare from the Eye: Oculomics as a Powerful Window to Systemic Health.

PURPOSE: To present a comprehensive framework for integrating oculomics to assess ocular and systemic health into coordinated health care delivery mod...

CBAM-ST-GCN: An enhanced DRL-based end-to-end visual navigation framework for mobile robot.

Visual-based navigation for mobile robot poses significant challenges due to limited visual perception and the presence of unforeseen dynamic obstacle...

Goals of Care Transitions following Postoperative Undertriage.

BACKGROUND: This study tests the hypothesis that postoperative undertriage of high-acuity patients to hospital floor units is associated with new post...

inMOTIFin: a lightweight end-to-end simulation software for regulatory sequences.

SUMMARY: The accurate development, assessment, interpretation, and benchmarking of bioinformatics frameworks for analyzing transcriptional regulatory ...

Multi-Source Temporal-Depth fusion for robust end-to-End visual odometry.

End-to-end visual odometry models have recently achieved localization accuracy on par with conventional techniques, while effectively reducing the occ...

ACFSENet: an adaptive cross-frequency global sparse encoding network for end-to-end EEG emotion recognition.

End-to-end EEG-based emotion recognition is attracting increasing attention due to its potential in human-computer interaction, mental health, and aff...