Journal of molecular neuroscience : MN
Apr 14, 2025
Glioblastoma (GBM) is a highly aggressive brain tumor with frequent recurrence, yet the molecular mechanisms driving recurrence remain poorly understood. Identifying recurrence-associated genes may improve prognosis and treatment strategies. We appli...
Acute ischemic stroke (AIS) patients with good collaterals tend to have better outcomes after endovascular therapy. Existing collateral scoring methods rely mainly on vessel segmentation and convolutional neural networks (CNNs), often ignoring bilate...
INTRODUCTION: Postpartum depression (PPD) has numerous adverse impacts on the families of new mothers and society at large. Early identification and intervention are of great significance. Although there are many existing machine learning classifiers...
BACKGROUND: Rotavirus is the leading cause of severe dehydrating diarrhea in children under 5 years worldwide. Timely diagnosis is critical, but access to confirmatory testing is limited in hospital settings. Machine learning (ML) models have shown p...
Insight into predictors of functioning after treatment for borderline personality disorder (BPD) is limited, despite growing recognition that more focus on other aspects of recovery, especially psychosocial functioning, is warranted. The present stud...
Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently available diagnostic biomarkers preclude early diagnosis, necessitating the development of alternative bio...
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 14, 2025
Auditory attention decoding from electroencephalogram (EEG) could infer to which source the user is attending in noisy environments. Decoding algorithms and experimental paradigm designs are crucial for the development of technology in practical appl...
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 13, 2025
AIM: The use of artificial intelligence (AI) and machine learning (ML) is increasingly widespread in radiation oncology. However, patient engagement to date has been poor. Respect for persons in the healthcare setting and the principle of informed co...
BACKGROUND: Pre-eclampsia (PE) contributes to more than one-fourth of all maternal deaths and half a million newborn deaths worldwide every year. Early screening and interventions can reduce PE incidence and related complications. We aim to 1) tempor...
INTRODUCTION: Integrating decision support mechanisms utilising artificial intelligence (AI) into medical radiation practice introduces unique challenges to accountability for patient care outcomes. AI systems, often seen as "black boxes," can obscur...