AIMC Topic: Machine Learning

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Using machine learning to identify pediatric ophthalmologists.

Journal of AAPOS : the official publication of the American Association for Pediatric Ophthalmology and Strabismus
This cross-sectional study used data from the American Academy of Ophthalmology IRIS Registry (Intelligent Research in Sight) and machine learning algorithms to identify pediatric ophthalmologists based on physician coding patterns. A random forest m...

Machine learning-assisted SERS sensor for fast and ultrasensitive analysis of multiplex hazardous dyes in natural products.

Journal of hazardous materials
The adulteration of natural products with multiple azo dyes has become a serious public health concern. Thus, on-site trace additive detection is demanded. Herein, we developed a gold-nanorod-based surface-enhanced Raman scattering (SERS) sensor to d...

Machine learning strengthened formulation design of pharmaceutical suspensions.

International journal of pharmaceutics
Many different formulation strategies have been investigated to oppose suboptimal treatment of long-term or chronic conditions, one of which are the nano- and microsuspensions prepared as long-acting injectables to prolong the release of an active ph...

Metrics for evaluation of automatic epileptogenic zone localization in intracranial electrophysiology.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
INTRODUCTION: Precise localization of the epileptogenic zone is critical for successful epilepsy surgery. However, imbalanced datasets in terms of epileptic vs. normal electrode contacts and a lack of standardized evaluation guidelines hinder the con...

Recent advances in culture medium design for enhanced production of monoclonal antibodies in CHO cells: A comparative study of machine learning and systems biology approaches.

Biotechnology advances
The production of monoclonal antibodies (mAbs) using Chinese Hamster Ovary (CHO) cells has revolutionized the treatment of numerous diseases, solidifying their position as a cornerstone of the biopharmaceutical industry. However, achieving maximum mA...

Evaluating ChatGPT's competency in radiation oncology: A comprehensive assessment across clinical scenarios.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: Artificial intelligence (AI) and machine learning present an opportunity to enhance clinical decision-making in radiation oncology. This study aims to evaluate the competency of ChatGPT, an AI language model, in interpreting clinical scenari...

A spatial machine learning approach to exploring the impacts of coal mining and ecological restoration on regional ecosystem health.

Environmental research
Ecosystem health is an important approach to measuring urban and regional sustainability. In previous studies, the spatiotemporal changes of ecosystem health have been addressed using comprehensive assessment index system. However, the quantitative c...

Machine learning approach in canine mammary tumour classification using rapid evaporative ionization mass spectrometry.

Analytical and bioanalytical chemistry
Rapid evaporative ionization mass spectrometry (REIMS) coupled with a monopolar handpiece used for surgical resection and combined with chemometrics has been previously explored by our research group (Mangraviti et al. in Int J Mol Sci 23(18):10562, ...

Machine learning outperforms the Canadian Triage and Acuity Scale (CTAS) in predicting need for early critical care.

CJEM
STUDY OBJECTIVE: This study investigates the potential to improve emergency department (ED) triage using machine learning models by comparing their predictive performance with the Canadian Triage Acuity Scale (CTAS) in identifying the need for critic...