AIMC Topic: Area Under Curve

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Optimization of Ganciclovir and Valganciclovir Starting Dose in Children by Machine Learning.

Clinical pharmacokinetics
BACKGROUND AND OBJECTIVES: Ganciclovir (GCV) and valganciclovir (VGCV) show large interindividual pharmacokinetic variability, particularly in children. The objectives of this study were (1) to develop machine learning (ML) algorithms trained on simu...

Machine learning improves prediction of postoperative outcomes after gastrointestinal surgery: a systematic review and meta-analysis.

Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
BACKGROUND: Machine learning (ML) approaches have become increasingly popular in predicting surgical outcomes. However, it is unknown whether they are superior to traditional statistical methods such as logistic regression (LR). This study aimed to p...

Predicting Pharmacokinetics of Drugs Using Artificial Intelligence Tools: A Systematic Review.

European journal of drug metabolism and pharmacokinetics
BACKGROUND AND OBJECTIVE: Pharmacokinetic studies encompass the examination of the absorption, distribution, metabolism, and excretion of bioactive compounds. The pharmacokinetics of drugs exert a substantial influence on their efficacy and safety. C...

Development and validation of a deep learning model for predicting postoperative survival of patients with gastric cancer.

BMC public health
BACKGROUND: Deep learning (DL), a specialized form of machine learning (ML), is valuable for forecasting survival in various diseases. Its clinical applicability in real-world patients with gastric cancer (GC) has yet to be extensively validated.

Enhancing the fairness of AI prediction models by Quasi-Pareto improvement among heterogeneous thyroid nodule population.

Nature communications
Artificial Intelligence (AI) models for medical diagnosis often face challenges of generalizability and fairness. We highlighted the algorithmic unfairness in a large thyroid ultrasound dataset with significant diagnostic performance disparities acro...

Prediction of Visual Field Progression with Baseline and Longitudinal Structural Measurements Using Deep Learning.

American journal of ophthalmology
PURPOSE: Identifying glaucoma patients at high risk of progression based on widely available structural data is an unmet task in clinical practice. We test the hypothesis that baseline or serial structural measures can predict visual field (VF) progr...

Artificial Intelligence to Determine Fetal Sex.

American journal of perinatology
OBJECTIVE:  This proof-of-concept study assessed how confidently an artificial intelligence (AI) model can determine the sex of a fetus from an ultrasound image.

Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis.

BMC medical informatics and decision making
BACKGROUND: Accurate diagnosis and early treatment are essential in the fight against lymphatic cancer. The application of artificial intelligence (AI) in the field of medical imaging shows great potential, but the diagnostic accuracy of lymphoma is ...

Treatment prediction with machine learning in prostate cancer patients.

Computer methods in biomechanics and biomedical engineering
There are various treatment modalities for prostate cancer, which has a high incidence. In this study, it is aimed to make predictions with machine learning in order to determine the optimal treatment option for prostate cancer patients. The study in...