AIMC Topic: Humans

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A deep image classification model based on prior feature knowledge embedding and application in medical diagnosis.

Scientific reports
Aiming at the problem of image classification with insignificant morphological structural features, strong target correlation, and low signal-to-noise ratio, combined with prior feature knowledge embedding, a deep learning method based on ResNet and ...

Predicting the Efficacy of Repeated Shockwave Lithotripsy for Treating Patients with Upper Urinary Tract Calculi Using an Artificial Neural Network Model.

Urology journal
PURPOSE: To establish a prediction model for repeated shockwave lithotripsy (SWL) efficacy to help choose an appropriate treatment plan for patients with a single failed lithotripsy, reducing their treatment burden.

How good are large language models at product risk assessment?

Risk analysis : an official publication of the Society for Risk Analysis
Product safety professionals must assess the risks to consumers associated with the foreseeable uses and misuses of products. In this study, we investigate the utility of generative artificial intelligence (AI), specifically large language models (LL...

The relationship between design-based lateralization, humeral bearing design, polyethylene angle, and patient-related factors on surgical complications after reverse shoulder arthroplasty: a machine learning analysis.

Journal of shoulder and elbow surgery
BACKGROUND: Technological advancements in implant design and surgical technique have focused on diminishing complications and optimizing performance of reverse shoulder arthroplasty (rTSA). Despite this, there remains a paucity of literature correlat...

The development of artificial intelligence in the histological diagnosis of Inflammatory Bowel Disease (IBD-AI).

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: Inflammatory bowel disease (IBD) includes Crohn's Disease (CD) and Ulcerative Colitis (UC). Correct diagnosis requires the identification of precise morphological features such basal plasmacytosis. However, histopathological interpretatio...

Time-Series MR Images Identifying Complete Response to Neoadjuvant Chemotherapy in Breast Cancer Using a Deep Learning Approach.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Pathological complete response (pCR) is an essential criterion for adjusting follow-up treatment plans for patients with breast cancer (BC). The value of the visual geometry group and long short-term memory (VGG-LSTM) network using time-s...

Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...

Using machine learning to unveil relevant predictors of adherence to recommended health-protective behaviors during the COVID-19 pandemic in Denmark.

Applied psychology. Health and well-being
What were relevant predictors of individuals' proclivity to adhere to recommended health-protective behaviors during the COVID-19 pandemic in Denmark? Applying machine learning (namely, lasso regression) to a repeated cross-sectional survey spanning ...

Machine learning models' assessment: trust and performance.

Medical & biological engineering & computing
The common black box nature of machine learning models is an obstacle to their application in health care context. Their widespread application is limited by a significant "lack of trust." So, the main goal of this work is the development of an evalu...

Artificial Intelligence vs. Doctors: Diagnosing Necrotizing Enterocolitis on Abdominal Radiographs.

Journal of pediatric surgery
BACKGROUND: Radiographic diagnosis of necrotizing enterocolitis (NEC) is challenging. Deep learning models may improve accuracy by recognizing subtle imaging patterns. We hypothesized it would perform with comparable accuracy to that of senior surgic...