Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11920257 | PMC |
| http://dx.doi.org/10.1038/s41416-025-02941-6 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Predicting Remission in Schizophrenia Using Machine Learning-Assessing the Impact of Sample Size and Predictor Overinclusion.
Acta Psychiatr Scand
September 2025
Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Introduction: Machine learning studies sometimes include a high number of predictors relative to the number of training cases. This increases the risk of overfitting and poor generalizability. A recent study hypothesized that between-trial heterogeneity precluded generalizable outcome prediction in schizophrenia from being achieved.
View Article and Find Full Text PDFOptimizing Workflow for Cone Beam Computed Tomography-Based Online Adaptive Radiation Therapy Toward Reduced Physician Involvement.
Adv Radiat Oncol
October 2025
Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiation Oncology and Radiotherapy, Augustenburger Platz 1, 13353 Berlin, Germany.
Purpose: To evaluate the impact of an optimized online adaptive radiation therapy workflow on physician involvement.
Methods And Materials: Data from a prospective phase 2 trial involving 34 prostate cancer patients treated with cone beam computed tomography (CBCT)-based online adaptive radiation therapy (62 Gy in 20 fractions) were analyzed. Manual interventions were required for 2 steps in the workflow: radiation therapy technologist review and adjustment of automatically segmented organs, guiding target segmentation, so-called "influencer," while physicians reviewed and refined the targets.
A Retrospective Multicenter Stratified Study on Perinatal Factors Influencing Neonatal Mortality in Preterm Infants in Kazakhstan.
Int J Pediatr
August 2025
Department of Neonatology, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
This study is aimed at evaluating the cumulative effect of postnatal risk factors on the survival of preterm neonates by examining key clinical parameters and complications across various gestational ages. A retrospective cohort study was conducted using data from 1109 neonates admitted to neonatal intensive care units at two tertiary regional hospitals in Kazakhstan between 2021 and 2024. Patients were classified into three groups based on gestational age: extremely preterm (< 28 weeks, = 223), very preterm (28-31 weeks, = 384), and moderate to late preterm (32-36 weeks, = 502).
View Article and Find Full Text PDFCorrigendum to: Impact of the COVID-19 outbreak on the field of hematopoietic cell transplantation in the Asia-Pacific region: APBMT Activity Survey 2020/2021 [Blood Cell Therapy. 2024; 7(4): 129-137. doi:10.31547/bct-2024-020].
Blood Cell Ther
August 2025
Japanese Data Center for Hematopoietic Cell Transplantation (JDCHCT), Department of Registry Science for Transplant and Cellular Therapy, Aichi Medical University School of Medicine, Nagakute, Japan.
[This corrects the article DOI: 10.31547/bct-2024-020.].
View Article and Find Full Text PDFArtificial Intelligence for Management of Major Depression: Initial Design, Progress, and Research Plans.
Alpha Psychiatry
August 2025
Information Sciences and Technology, George Mason University, Fairfax, VA 22030, USA.
Background: Herein, we report on the initial development, progress, and future plans for an autonomous artificial intelligence (AI) system designed to manage major depressive disorder (MDD). The system is a web-based, patient-facing conversational AI that collects medical history, provides presumed diagnosis, recommends treatment, and coordinates care for patients with MDD.
Methods: The system includes seven components, five of which are complete and two are in development.