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Surveys

Latest AI and machine learning research in surveys for healthcare professionals.

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Head-down tilt lithotomy position and well-leg compartment syndrome: An international survey of current practice.

AIM: Well-leg compartment syndrome (WLCS) is a serious complication of prolonged surgery in the head...

On the use of natural language processing to implement the target trial framework using unstructured data from the electronic health record.

The increasing availability and accessibility of electronic health record (EHR) data has made it a r...

Quantifying Healthcare Provider Perceptions of a Novel Deep Learning Algorithm to Predict Sepsis: Electronic Survey.

IMPORTANCE: Sepsis is a major cause of morbidity and mortality, with early intervention shown to imp...

Addressing Workforce and Ethical Gaps in AI-Driven Mental Health Care: A Response to Higgins and Wilson.

Artificial intelligence (AI)-based clinical decision support systems (CDSS) hold great promise for m...

Assessing Clinician Consistency in Wound Tissue Classification and the Value of AI-Assisted Quantification: A Cross-Sectional Study.

This study investigated the relationship between clinician assessments and the AI-generated scores, ...

Development and Validation of a Scale for Nurses' Ethical Awareness in The Use of Artificial Intelligence: A Methodological Study.

The integration of artificial intelligence in nursing practice presents significant ethical challeng...

Artificial Intelligence and Machine Learning Innovations to Improve Design and Representativeness in Oncology Clinical Trials.

The integration of artificial intelligence (AI) and machine learning (ML) in oncology clinical trial...

Evaluating algorithmic bias on biomarker classification of breast cancer pathology reports.

OBJECTIVES: This work evaluated algorithmic bias in biomarkers classification using electronic patho...

Sharing patient technology preferences with care networks: Stakeholders' views of the "Let's Talk Tech" decision aid for dementia care.

BackgroundLet's Talk Tech (LTT) is a self-administered web intervention for people with memory loss ...

Needs of bereaved families of patients with cancer towards artificial intelligence in palliative care: A web-based survey.

PURPOSE: Artificial intelligence (AI) systems in palliative care have garnered attention and popular...

Concise multi-class anxiety disorder risk assessment: A novel advanced machine learning approach.

Rapidly assessing anxiety disorder risk is crucial for effective mental health screen and interventi...

PRECISE framework: Enhanced radiology reporting with GPT for improved readability, reliability, and patient-centered care.

BACKGROUND: The PRECISE framework, defined as Patient-Focused Radiology Reports with Enhanced Clarit...

Accelerating autism spectrum disorder care: A rapid review of data science applications in diagnosis and intervention.

Integrating data science techniques, including machine learning, natural language processing, and bi...

RoBIn: A Transformer-based model for risk of bias inference with machine reading comprehension.

OBJECTIVE: Scientific publications are essential for uncovering insights, testing new drugs, and inf...

Automatic cough detection via a multi-sensor smart garment using machine learning.

Coughing behavior is associated with conditions such as sleep apnea, asthma, and chronic obstructive...

Combining Deep Data-Driven and Physics-Inspired Learning for Shear Wave Speed Estimation in Ultrasound Elastography.

The shear wave elastography (SWE) provides quantitative markers for tissue characterization by measu...

Automatic implicit motive codings are at least as accurate as humans' and 99% faster.

Implicit motives, nonconscious needs that influence individuals' behaviors and shape their emotions,...

The Large Language Models on Biomedical Data Analysis: A Survey.

With the rapid development of Large Language Model (LLM) technology, it has become an indispensable ...

Assessing and improving reliability of neighbor embedding methods: a map-continuity perspective.

Visualizing high-dimensional data is essential for understanding biomedical data and deep learning m...

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