AIMC Topic: Humans

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Rethinking feature reproducibility in radiomics: the elephant in the dark.

European radiology experimental
In radiomics, features are often linked to biomarkers and are generally expected to be reproducible, as reproducibility is considered a prerequisite for developing predictive models in clinical applications. However, this perspective overlooks featur...

Lung lobe segmentation: performance of open-source MOOSE, TotalSegmentator, and LungMask models compared to a local in-house model.

European radiology experimental
BACKGROUND: Lung lobe segmentation is required to assess lobar function with nuclear imaging before surgical interventions. We evaluated the performance of open-source deep learning-based lung lobe segmentation tools, compared to a similar nnU-Net mo...

Computational approaches for toxicology and Pharmacokinetic properties prediction.

Journal of pharmacokinetics and pharmacodynamics
Pharmacokinetics and toxicological studies how the body reacts to a specific administered substance, such as a drug, toxin, or food. Each substance experiences these four steps: absorption, distribution, metabolism, and excretion, which are the main ...

Utilisation of AI-driven chatbots for perioperative health information seeking: a descriptive qualitative study of orthopaedic patients and family members.

BMJ open
OBJECTIVE: This study aimed to explore orthopaedic patients' and families' experiences with artificial intelligence (AI)-driven chatbots for perioperative health information, focusing on usability, effectiveness and perceptions.

Quality and efficiency of integrating customised large language model-generated summaries versus physician-written summaries: a validation study.

BMJ open
OBJECTIVES: To compare the quality and time efficiency of physician-written summaries with customised large language model (LLM)-generated medical summaries integrated into the electronic health record (EHR) in a non-English clinical environment.

Development of a Clinical Clerkship Mentor Using Generative AI and Evaluation of Its Effectiveness in a Medical Student Trial Compared to Student Mentors: 2-Part Comparative Study.

JMIR medical education
BACKGROUND: At the beginning of their clinical clerkships (CCs), medical students face multiple challenges related to acquiring clinical and communication skills, building professional relationships, and managing psychological stress. While mentoring...

How Well Do ChatGPT and Claude Perform in Study Selection for Systematic Review in Obstetrics.

Journal of medical systems
The use of generative AI in systematic review workflows has gained attention for enhancing study selection efficiency. However, evidence on its screening performance remains inconclusive, and direct comparisons between different generative AI models ...

Technological evolution and research frontiers of robot-assisted ultrasound examination: a bibliometric exploration.

Journal of robotic surgery
Technological innovations in robot-assisted ultrasound (RAUS) have remarkably advanced the development of precision and intelligent medical imaging diagnosis. This study aims to use bibliometric methods to systematically analyze the technological evo...

Detecting, Characterizing, and Mitigating Implicit and Explicit Racial Biases in Health Care Datasets With Subgroup Learnability: Algorithm Development and Validation Study.

Journal of medical Internet research
BACKGROUND: The growing adoption of diagnostic and prognostic algorithms in health care has led to concerns about the perpetuation of algorithmic bias against disadvantaged groups of individuals. Deep learning methods to detect and mitigate bias have...

Advancements in deep learning for image-guided tumor ablation therapies: a comprehensive review.

Progress in biomedical engineering (Bristol, England)
Image-guided tumor ablation (IGTA) has revolutionized modern oncological treatments by providing minimally invasive options that ensure precise tumor eradication with minimal patient discomfort. Traditional techniques such as ultrasound (US), compute...