AIMC Topic: Humans

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Surgical phase and instrument recognition: how to identify appropriate dataset splits.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning approaches can only be reliably evaluated if training, validation, and test data splits are representative and not affected by the absence of classes. Surgical workflow and instrument recognition are two tasks that are compl...

Competency in Robotic Surgery: Standard Setting for Robotic Suturing Using Objective Assessment and Expert Evaluation.

Journal of surgical education
OBJECTIVE: Surgical skill assessment tools such as the End-to-End Assessment of Suturing Expertise (EASE) can differentiate a surgeon's experience level. In this simulation-based study, we define a competency benchmark for intraoperative robotic sutu...

Impaired perception of a partner's synchronizing behavior reduces positive attitude toward humanoid robot in schizophrenia patients.

Schizophrenia research
As interpersonal synchrony plays a key role in building rapport, the perception of another agent's synchronizing behavior could be an important feature to assess, especially with patients with social deficits such as in schizophrenia. Twenty-four sch...

Fall risk classification with posturographic parameters in community-dwelling older adults: a machine learning and explainable artificial intelligence approach.

Journal of neuroengineering and rehabilitation
BACKGROUND: Computerized posturography obtained in standing conditions has been applied to classify fall risk for older adults or disease groups. Combining machine learning (ML) approaches is superior to traditional regression analysis for its abilit...

Development and prognostic validation of a three-level NHG-like deep learning-based model for histological grading of breast cancer.

Breast cancer research : BCR
BACKGROUND: Histological grade is a well-known prognostic factor that is routinely assessed in breast tumours. However, manual assessment of Nottingham Histological Grade (NHG) has high inter-assessor and inter-laboratory variability, causing uncerta...

Protocol for metadata and image collection at diabetic foot ulcer clinics: enabling research in wound analytics and deep learning.

Biomedical engineering online
BACKGROUND: The escalating impact of diabetes and its complications, including diabetic foot ulcers (DFUs), presents global challenges in quality of life, economics, and resources, affecting around half a billion people. DFU healing is hindered by hy...

Outcomes of robot-assisted laparoscopic extended pelvic lymph node dissection for prostate Cancer.

BMC urology
INTRODUCTION: Extended pelvic lymph node dissection (ePLND) in men undergoing robot-assisted laparoscopic radical prostatectomy (RARP) is a widely used procedure. However, little is known about anatomical site-specific yields and subsequent metastati...

Survival prediction of glioblastoma patients using modern deep learning and machine learning techniques.

Scientific reports
In this study, we utilized data from the Surveillance, Epidemiology, and End Results (SEER) database to predict the glioblastoma patients' survival outcomes. To assess dataset skewness and detect feature importance, we applied Pearson's second coeffi...

An artificial intelligence approach to predicting personality types in dogs.

Scientific reports
Canine personality and behavioural characteristics have a significant influence on relationships between domestic dogs and humans as well as determining the suitability of dogs for specific working roles. As a result, many researchers have attempted ...

Artificial intelligence model GPT4 narrowly fails simulated radiological protection exam.

Journal of radiological protection : official journal of the Society for Radiological Protection
This study assesses the efficacy of Generative Pre-Trained Transformers (GPT) published by OpenAI in the specialised domains of radiological protection and health physics. Utilising a set of 1064 surrogate questions designed to mimic a health physics...