AIMC Topic: Humans

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Empathy training for counselling novices: A randomized controlled trial using machine learning and natural language processing.

Psychology and psychotherapy
OBJECTIVE: Empathy is a critical skill for effective counselling, yet novice counsellors often struggle to develop it. Traditional training methods may not sufficiently address the complexities of empathic development. This study aims to develop and ...

Advancements and future trends in machine learning for lung cancer: a comprehensive bibliometric analysis.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
BACKGROUND: In recent years, significant progress has been made in lung cancer screening, diagnosis, and treatment with the continuous development of machine learning (ML).

Factors associated with coronary artery bypass grafting excess readmission ratios.

Surgery
BACKGROUND: The Hospital Readmissions Reduction Program determines Medicare readmission penalties through risk-adjusted excess readmissions ratios. This study uses interpretable machine learning to identify associations with coronary artery bypass gr...

Maximizing Lung Cancer Screening in High-Risk Population Leveraging ML-Developed Risk-Prediction Algorithms: Danish Retrospective Validation of LungFlag.

Clinical lung cancer
BACKGROUND: Early detection of lung cancer (LC) is crucial for curative treatment, but current screening methods face challenges due to high costs and poor adherence. Artificial intelligence tools, such as the LungFlag model, uses routine clinical da...

Predicting clinical prognosis in gastric cancer using deep learning-based analysis of tissue pathomics images.

Computer methods and programs in biomedicine
OBJECTIVE: Evaluate the utility of a machine learning-based pathomics model in predicting overall survival (OS) post-surgery for gastric cancer patients.

Automated phenotypic analysis and classification of drug-treated cardiomyocytes via synergized time-lapse holographic imaging and deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Predicting cardiovascular risk is critical for the therapy and control of cardiovascular illnesses. This work studies screening the toxicity of three drugs, (E-4031, isoprenaline, and sertindole) with various concentrations ...

Cognitive Lab: A dataset of biosignals and HCI features for cognitive process investigation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Attention, cognitive workload/fatigue, and emotional states significantly influence learning outcomes, cognitive performance, and human-machine interactions. However, existing assessment methodologies fail to fully capture t...

Lesion boundary detection for skin lesion segmentation based on boundary sensing and CNN-transformer fusion networks.

Artificial intelligence in medicine
Traditional convolutional neural networks often struggle to capture global information and handle ambiguous boundaries during complex skin lesion segmentation tasks. To tackle this challenge, we proposed MPBA-Net, a hybrid network that integrates mul...

Large language models for the screening step in systematic reviews in dentistry.

Journal of dentistry
OBJECTIVES: This study assessed the performance of chatbots in the screening step of a systematic review (SR) with an exemplary focus on tooth segmentation on dental radiographs using artificial intelligence (AI).

Macy Foundation Innovation Report Part II: From Hype to Reality: Innovators' Visions for Navigating AI Integration Challenges in Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
PURPOSE: Artificial intelligence (AI) promises to significantly impact medical education, yet its implementation raises important questions about educational effectiveness, ethical use, and equity. In the second part of a 2-part innovation report, wh...