Care of terminally ill / Palliative care

SilicoXplore: An integrated cloud platform coupling machine learning with physics-based modelling for end-to-end drug discovery, applied to the computational prioritisation of putative New Delhi metallo-β-lactamase-1 binders.

Modern drug discovery joins machine learning with physics-based simulation, but building such a pipeline needs Linux administration, dependency management, format conversion and scripting, which keeps out many of the chemists and biologists who ask the questions. We describe SilicoXplore, a cloud-hosted platform of 31 interoperable modules covering structure preparation, five docking engines, de n...

Development of a YOLO-guided automated (microplastic) particle analysis workflow.

Microplastics (MPs) are an emerging pollutant of global concern, creating an urgent need for rapid and accurate monitoring workflows. Deep learning-based computer vision has demonstrated strong performance in finding particles in microscopy images, but its use as a front-end module for automated IR/Raman microscope-based MP analysis remains insufficiently developed, particularly in workflows that ...

From assistant to collaborator: A systematic review of the evolution of artificial intelligence in end-stage renal disease care and management.

We aimed to systematically analyze the historical evolution of artificial intelligence (AI) in end-stage renal disease (ESRD) management and propose a...

Feasibility of a Stool State Check App Using AI During Bowel Preparation Before Colonoscopy: Multicenter Prospective Study (SCAN Study).

BACKGROUND: Optimal bowel preparation (BP) is crucial for a successful colonoscopy. Although multiple factors influence BP quality, including patient ...

Machine Learning of Temperature-Dependent Chemical Kinetics Using Parallel Droplet Microreactors.

Temperature is a fundamental regulator of chemical and biochemical kinetics, yet capturing nonlinear thermal effects directly from experimental data r...

Bridging the gap: predicting early contingency management outcomes.

Background: Contingency management (CM) is a psychosocial treatment used to improve socially significant behaviors. Its efficacy has been demonstrated...

When end users can build: AI-assisted application development and the new accountability gap in digital health.

Generative artificial intelligence (AI) is dramatically changing the division of labor in digital health innovation. Until recently, a frontline healt...

Fully automated deep learning for the identification and classification of dental implant brands from multimodal radiographic images.

OBJECTIVES: Accurate radiographic identification of dental implant systems is essential for effective clinical management; however, manual assessment ...

Influence of artificial intelligence on the performance of endosonographers in detection of solid pancreatic tumors: a tandem randomized video study.

BACKGROUND: This study aimed to evaluate the influence of a pre-commercial artificial intelligence (AI)-based software system on endosonographers' per...

Prognostication in End-Stage Kidney Disease: Tools, Evidence, and Clinical Applications.

Prognostication in end-stage kidney disease is fundamental to person-centered care and shared decision-making. This review summarizes the current evid...

A Scoping Review of Interpretable AI Model Approaches in Echocardiography: Frameworks, Model Types, Explanation Strategies, and Evaluation Practices.

Echocardiography is a central modality for cardiac diagnosis; rising clinical demand and advances in machine learning have accelerated AI development ...

A toolbox to optimize and scale up microfluidic production of lipid-based nanoparticles.

The use of nanoparticles (NPs) for delivery, particularly for nucleic acid-based therapeutics has become a central determinant of therapeutic efficacy...

Optimization of a bionic end-effector for automated cherry tomato harvesting using Response Surface Methodology and Box-Behnken design.

Harvesting cherry tomatoes is a labor-intensive and time-consuming endeavor. The implementation of robots for this task represents an effective soluti...

Real-World Barriers to and Facilitators of Implementing AI-Based Clinical Decision Support Systems: Scoping Review.

BACKGROUND: Widespread and sustained uptake of AI-based clinical decision support systems (CDSSs) in real-world health care settings is uncommon, desp...

End-To-End Discovery of MOFs for Ambient CH4 Adsorption.

We report an end-to-end computational-experimental workflow for the discovery of metal-organic frameworks (MOFs), demonstrated by the computational de...

Machine learning-based prediction of postoperative restenosis risk following direct repair of paediatric coarctation of the aorta.

OBJECTIVES: Coarctation of the aorta is a congenital cardiovascular disease with focal aortic luminal narrowing, and paediatric patients face a high p...

Critical Care-Specific vs General-Purpose Large Language Models in Emergency Intensive Care Unit Diagnosis: Single-Center Retrospective Paired Comparative Study.

BACKGROUND: The emergency intensive care unit (EICU) manages the most critically ill patients, where rapid and accurate diagnosis is essential yet cha...

Deep learning for imaging-free voids detection by ultrasonic data: bridging numerical data and model experiments.

Non-destructive testing (NDT) based on ultrasonics is widely used for internal defect detection. To enhance the efficiency of defect detection, Deep L...

Heterogeneous Treatment Effects of Renal Replacement Therapy in Critically Ill Patients: A Multicenter Observational Study Using a Japanese ICU Registry.

OBJECTIVE: Randomized trials evaluating the timing of renal replacement therapy (RRT) have informed current practice toward more conservative initiati...

Using Natural Language Processing to Identify Adverse Drug Events Characterized by Medication Replacement in Primary Care Electronic Medical Records: Algorithm and Validation Study.

BACKGROUND: Health care systems generate vast amounts of unstructured text, such as clinical notes, which capture nuanced patient experiences, clinica...