AIMC Topic: ROC Curve
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An application of deep learning model InceptionTime to predict nausea, vomiting, diarrhoea, and constipation using the gastro-intestinal pacemaker activity drug database (GIPADD).
Scientific reports
Apr 16, 2025
The accurate preclinical prediction of adverse drug reactions (ADRs), such as nausea and vomiting, remains a challenge. The Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) ( http://www.gutrhythm.com/public_database ) is a new source of el...
Digestive System Diseases
Predictive Learning Models
Vomiting
Databases, Pharmaceutical
Biological Clocks
Electrodiagnosis
Drug-Related Side Effects and Adverse Reactions
Humans
Gastrointestinal Tract
Reproducibility of Results
Deep Learning
Diarrhea
Constipation
Big Data
ROC Curve
Nausea
Area Under Curve
Feasibility Studies
A prediction model of pediatric bone density from plain spine radiographs using deep learning.
Scientific reports
Apr 15, 2025
Osteoporosis, a bone disease characterized by decreased bone mineral density (BMD) resulting in decreased mechanical strength and an increased fracture risk, remains poorly understood in children. Herein, we developed/validated a deep learning-based ...
Detection of diabetic macular oedema patterns with fine-grained image categorisation on optical coherence tomography.
BMJ open ophthalmology
Apr 15, 2025
PURPOSE: To develop an artificial intelligence (AI) system for detecting pathological patterns of diabetic macular oedema (DME) with fine-grained image categorisation using optical coherence tomography (OCT) images.
Development and validation of a nomogram model of lung metastasis in breast cancer based on machine learning algorithm and cytokines.
BMC cancer
Apr 14, 2025
BACKGROUND: The relationship between cytokines and lung metastasis (LM) in breast cancer (BC) remains unclear and current clinical methods for identifying breast cancer lung metastasis (BCLM) lack precision, thus underscoring the need for an accurate...
Machine learning-based disease risk stratification and prediction of metabolic dysfunction-associated fatty liver disease using vibration-controlled transient elastography: Result from NHANES 2021-2023.
BMC gastroenterology
Apr 14, 2025
BACKGROUND: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a common chronic liver disease and represents a significant public health issue. Nevertheless, current risk stratification methods remain inadequate. The study aimed to use m...
Comparative study of XGBoost and logistic regression for predicting sarcopenia in postsurgical gastric cancer patients.
Scientific reports
Apr 14, 2025
The use of machine learning (ML) techniques, particularly XGBoost and logistic regression, to predict sarcopenia among postsurgical gastric cancer patients has gained significant attention in recent research. Sarcopenia, characterized by the progress...
A radiomics approach to distinguish Progressive Supranuclear Palsy Richardson's syndrome from other phenotypes starting from MR images.
Computer methods and programs in biomedicine
Apr 13, 2025
BACKGROUND AND OBJECTIVE: Progressive Supranuclear Palsy (PSP) is an uncommon neurodegenerative disorder with different clinical onset, including Richardson's syndrome (PSP-RS) and other variant phenotypes (vPSP). Recognising the clinical progression...
Hybrid of DSR-GAN and CNN for Alzheimer disease detection based on MRI images.
Scientific reports
Apr 13, 2025
In this paper, we propose a deep super-resolution generative adversarial network (DSR-GAN) combined with a convolutional neural network (CNN) model designed to classify four stages of Alzheimer's disease (AD): Mild Dementia (MD), Moderate Dementia (M...
Development of a machine learning-based diagnostic model using hematological parameters to differentiate periductal mastitis from granulomatous lobular mastitis.
Science progress
Apr 13, 2025
ObjectiveNonpuerperal mastitis (NPM) is an inflammatory condition, including periductal mastitis (PDM) and granulomatous lobular mastitis (GLM). The clinical manifestations of PDM and GLM are highly similar, posing significant challenges in their dif...
Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers.
Scientific reports
Apr 12, 2025
Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. Cancer screening in the healthy population involves an initial risk stratification step to determine the...
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