Risk Management

Protocol for creating representations of molecular structures using a polymer-specific decoder.

To supply chemical structures of polymers for machine learning applications, decoding is necessary. Here, we present a protocol for generating polymer fingerprints (PFPs), which are representations of molecular structures, using a polymer-specific decoder. We outline steps for downloading, installing, and basic application of the software. Moreover, we present procedures for processing and analyzi...

Consolidated Reporting Guidelines for Prognostic and Diagnostic Machine Learning Models (CREMLS).

The number of papers presenting machine learning (ML) models that are being submitted to and published in the Journal of Medical Internet Research and other JMIR Publications journals has steadily increased. Editors and peer reviewers involved in the review process for such manuscripts often go through multiple review cycles to enhance the quality and completeness of reporting. The use of reportin...

REFORMS: Consensus-based Recommendations for Machine-learning-based Science.

Machine learning (ML) methods are proliferating in scientific research. However, the adoption of these methods has been accompanied by failures of val...

Development of an Artificial Intelligence Teaching Assistant System for Undergraduate Nursing Students: A Field Testing Study.

Keeping students engaged and motivated during online or class discussion may be challenging. Artificial intelligence has potential to facilitate activ...

Research on a machine learning-based adaptive and efficient screening model for psychological symptoms of community correctional prisoners.

Community correction institutions in China frequently employ the Symptom Checklist-90 (SCL-90) and the health survey brief (SF-12) as primary tools fo...

Preclinical identification of acute coronary syndrome without high sensitivity troponin assays using machine learning algorithms.

Preclinical management of patients with acute chest pain and their identification as candidates for urgent coronary revascularization without the use ...

Protocol to identify biomarkers in patients with post-COVID condition using multi-omics and machine learning analysis of human plasma.

Here, we present a workflow for analyzing multi-omics data of plasma samples in patients with post-COVID condition (PCC). Applicable to various diseas...

Large Language Models and User Trust: Consequence of Self-Referential Learning Loop and the Deskilling of Health Care Professionals.

As the health care industry increasingly embraces large language models (LLMs), understanding the consequence of this integration becomes crucial for ...

Exploring Human-Exoskeleton Interaction Dynamics: An In-Depth Analysis of Knee Flexion-Extension Performance across Varied Robot Assistance-Resistance Configurations.

Knee rehabilitation therapy after trauma or neuromotor diseases is fundamental to restore the joint functions as best as possible, exoskeleton robots ...

Using deep learning to optimize the prostate MRI protocol by assessing the diagnostic efficacy of MRI sequences.

PURPOSE: To explore diagnostic deep learning for optimizing the prostate MRI protocol by assessing the diagnostic efficacy of MRI sequences.

Energy Expenditure Prediction from Accelerometry Data Using Long Short-Term Memory Recurrent Neural Networks.

The accurate estimation of energy expenditure from simple objective accelerometry measurements provides a valuable method for investigating the effect...

ChatGPT/GPT-4 (large language models): Opportunities and challenges of perspective in bariatric healthcare professionals.

ChatGPT/GPT-4 is a conversational large language model (LLM) based on artificial intelligence (AI). The potential application of LLM as a virtual assi...

Protocol to explain support vector machine predictions via exact Shapley value computation.

Shapley values from cooperative game theory are adapted for explaining machine learning predictions. For large feature sets used in machine learning, ...

Artificial intelligence in clinical nutrition and dietetics: A brief overview of current evidence.

The rapid surge in artificial intelligence (AI) has dominated technological innovation in today's society. As experts begin to understand the potentia...

Unraveling the distinction between depression and anxiety: A machine learning exploration of causal relationships.

OBJECTIVE: Depression and anxiety, prevalent coexisting mood disorders, pose a clinical challenge in accurate differentiation, hindering effective hea...

Efficient cluster-based routing protocol for wireless sensor networks by using collaborative-inspired Harris Hawk optimization and fuzzy logic.

In wireless sensor networks, the implementation of clustering and routing protocols has been crucial in prolonging the network's operational duration ...

Physiological data for affective computing in HRI with anthropomorphic service robots: the AFFECT-HRI data set.

In human-human and human-robot interaction, the counterpart influences the human's affective state. Contrary to humans, robots inherently cannot respo...

ROBot-assisted physical training of older patients during acUte hospitaliSaTion-study protocol for a randomised controlled trial (ROBUST).

BACKGROUND: During hospitalisation, older patients spend most of their time passive in bed, which increases the risk of functional decline and negativ...

Robot-assisted support combined with electrical stimulation for the lower extremity in stroke patients: a systematic review.

. The incidence of stroke rising, leading to an increased demand for rehabilitation services. Literature has consistently shown that early and intensi...

Liability Exposure of Clinicians in Artificial Intelligence-Driven Healthcare.