A vision transformer deep learning model for assessing pediatric ileocolic intussusception severity using ultrasound images

Applications of traditional machine learning and deep learning algorithms in obesity prediction or classification: a systematic review of comparative performance

Mehrdad Jamali, Meysam Zarezadeh, Mohammad Vesal Bideshki, Mohamed Khalifa, Michelle Cavaleri, Ahmad Saedisomeolia, et al.

Evaluating large language models for assessment of psychosis risk

Taiyu Zhu, Alexander Tashevski, Maxime Taquet, Matilda Azis, Tia Jani, Matthew R. Broome, et al.

Abstract Psychosis prevention relies on early detection of individuals at clinical high risk for psychosis (CHR-P). The effectiveness of the CHR-P state is constrained, in part, due to clinical assessments requiring specialist interpretation of narrative interviews, limiting scal…Read more

Enhancing out-of-hospital emergency care via lexical machine learning modeling of chief complaints

Aaron C. Weidman, Remle P. Crowe, Ali Treichel, Francis X. Guyette, David D. Salcido

Advancing genomics and integration of multi-omics for precision oncology using quantum machine learning

Ji-Yong Sung, Jae-Ho Cheong

Abstract Cancer multi-omics faces challenges in handling the scale, complexity, and heterogeneity of multi-omics data, limiting progress in variant interpretation, tumor classification, and modeling cancer evolution. Quantum computing offers a new paradigm using superposition, en…Read more

Simulation of covariate and concept drift in machine learning hospital admission prediction from emergency triage

Ethan Williams, Toshi Sinha, Matthew Summerscales, Yogesan Kanagasingam

Abstract Machine learning models that predict hospital admission at triage may support patient flow forecasting, yet the effects of covariate drift, concept drift, and retraining on long-term performance are poorly understood. We developed an Extreme Gradient Boosting (XGBoost) m…Read more

Advanced machine learning-based screening for primary aldosteronism with plasma steroids, potassium, and renin

Wenyu Zhang, Christina Pamporaki, René Jäkel, Georgiana Constantinescu, Mirko Peitzsch, Manuel Schulze, et al.

Abstract Commonly used screening tests for primary aldosteronism (PA) provide suboptimal diagnostic accuracy, particularly with antihypertensive medication use. This study utilized three datasets totaling 1380 patients with and without PA to develop machine learning models for sc…Read more