Care of terminally ill / Palliative care

Design and implementation of an end-to-end AI-driven colonoscopy recall workflow at scale.

OBJECTIVES: To develop a large-language-model (LLM)-centric workflow flow extraction and migration of clinician-documented colonoscopy recall recommendations from unstructured reports and letters during an enterprise-wide electronic health record (EHR) transition. MATERIALS AND METHODS: A multi-stage workflow [Optical Character Recognition (OCR) -> LLM -> structured fields] was built around a cent...

Homogeneous image-based digital immunoassays with high error tolerance.

There is a significant global health need to translate more in vitro diagnostic tests from clinical laboratories to field-based applications, including point-of-care and self-administered test formats. These applications typically require smaller sample sizes, limit sample processing and measurement capabilities, and introduce greater handling variability. Error tolerance is one of the most critic...

Applicable Scenarios, Desired Features, and Risks of AI Psychotherapists in Depression Treatment From the Patient's Perspective: Exploratory Qualitative Study.

BACKGROUND: Depression is a pervasive global mental health issue, yet access to trained professionals remains severely limited. With the rapid advance...

Machine Learning Interpretability to Assess the Association Between Time in Tight Range and Mortality in Cardiogenic Shock.

BACKGROUND: Cardiogenic shock (CS) is a critical condition of end-organ hypoperfusion with high mortality. Fluctuations in blood glucose (BG) levels m...

[Current applications and prospects of artificial intelligence in perioperative comprehensive management for gastrointestinal surgery].

The shift from the traditional empirical approach to a more data-driven method in the diagnosis and treatment of GI cancers is significant due to adva...

End-to-End Image Compression With Segmentation Guided Dual Coding for Wind Turbines.

Transferring large volumes of high-resolution images during wind turbine inspections introduces a bottleneck in assessing and detecting severe defects...

AI in Point-of-Care Imaging for Clinical Decision Support: Systematic Review of Diagnostic Accuracy, Task-Shifting, and Explainability.

BACKGROUND: Artificial intelligence (AI) integrated with point-of-care imaging is a promising approach to expand access in settings with limited speci...

DDA-BERT: end-to-end training for data-dependent acquisition mass spectrometry-based proteomics.

Peptide-spectrum match (PSM) rescoring is critical for accurate peptide identification in data-dependent acquisition (DDA)-based proteomics. Existing ...

Screening of metabolic-related biomarkers linking intervertebral disc degeneration and type 2 diabetes based on comprehensive bioinformatics analysis and machine learning.

BACKGROUND: Intervertebral disc degeneration (IVDD) is a prominent etiology of lower back pain. Type 2 diabetes (T2D), the most prevalent metabolic di...

Algorithms-Driven Optoelectronic Devices for Three-Dimensional Imaging.

Three-dimensional (3D) imaging captures spatial depth and multidimensional attributes, enabling precise scene reconstruction for diverse applications ...

League of Radiologists-an End-to-End AI Framework for Scalable and Gamified Radiology Education: A Pilot Implementation in Chest Radiography.

Traditional radiology education is constrained by a restricted apprenticeship model and a scarcity of datasets structured for building artificial inte...

iPalmT: a new paradigm for palmitoyltransferase discovery via end-to-end deep learning.

Protein S-palmitoylation, a dynamic lipid modification, is essential for protein stability, trafficking, and signaling; dysregulated palmitoyltransfer...

Echo-SMADS: A hierarchical planning model for predicting ejection fraction using echocardiography.

BACKGROUND AND OBJECTIVE: Current deep learning approaches for predicting ejection fraction primarily rely on end-to-end regression. While effective i...

Molecular Biomarkers and Risk Prediction Models for Acute Kidney Injury Following Liver Transplantation: A Review.

Liver transplantation is the definitive treatment for end-stage liver disease; however, postoperative acute kidney injury (AKI) affects 30%-70% of rec...

Prospective Data Curation Enables High-Performance Artificial Intelligence for Diabetic Retinopathy Screening in a Resource-Limited Setting.

PURPOSE: To determine whether a high-quality, prospectively curated dataset can, by itself, enable the development of robust and clinically effective ...

Development of a Contextualized, Research-Based Flemish Assessment Framework for Digital Care, Assistance, and Support: Delphi Study.

BACKGROUND: The rapid evolution of digital technologies has transformed health, mental health, and social care, offering new modalities of digital car...

Deep learning-based gait phase detection using shank-mounted IMU data: Classification approach.

Gait is a key indicator for assessing an individual's mobility and overall health, and accurate detection of gait cycle phases is essential for precis...

Transfer Learning and Machine Learning for Training Five-Year Survival Prognostic Models in Early Breast Cancer: Development and Validation Study.

BACKGROUND: Prognostic information is essential for decision-making in breast cancer management. In recent years, trials and clinical practice have em...

ToxCML: A Hybrid mfCoQ-RASAR-Based Platform Integrating Consensus QSAR and Read-Across for Comprehensive Multi-End Point Toxicity Assessment.

Computational in silico methods offer a powerful alternative to animal-based toxicity testing, which remains time-consuming, expensive, and ethically ...

How Hospice and Palliative Care Are Portrayed in Artificial Intelligence-Generated Images: A Content Analysis.

BACKGROUND: AI-generated images can support or impede health communication efforts and influence perceptions of health-related topics, making it impor...