AIMC Topic: Humans

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Modernizing Neuro-Oncology: The Impact of Imaging, Liquid Biopsies, and AI on Diagnosis and Treatment.

International journal of molecular sciences
Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are among the most challenging malignancies due to their high mortality rates and complex neurological effects. Despite advancements in surgery and chemor...

Robust Automated Harmonization of Heterogeneous Data Through Ensemble Machine Learning: Algorithm Development and Validation Study.

JMIR medical informatics
BACKGROUND: Cohort studies contain rich clinical data across large and diverse patient populations and are a common source of observational data for clinical research. Because large scale cohort studies are both time and resource intensive, one alter...

Results comparison of cervical cancer early detection using cerviray ® with VIA test.

BMC research notes
OBJECTIVES: This study investigates the performance of artificial intelligence (AI) technology, namely Cerviray AI, compared with Cerviray expert, aiming to compare its sensitivity, specificity, positive predictive value (PPV), and area under the rec...

Deep learning-based synthetic CT for dosimetric monitoring of combined conventional radiotherapy and lattice boost in large lung tumors.

Radiation oncology (London, England)
PURPOSE: Conventional radiotherapy (CRT) has limited local control and poses a high risk of severe toxicity in large lung tumors. This study aimed to develop an integrated treatment plan that combines CRT with lattice boost radiotherapy (LRT) and mon...

Death risk prediction model for patients with non-traumatic intracerebral hemorrhage.

BMC medical informatics and decision making
BACKGROUND: This study aimed to assess the risk of death from non-traumatic intracerebral hemorrhage (ICH) using a machine learning model.

Ensemble machine learning models for lung cancer incidence risk prediction in the elderly: a retrospective longitudinal study.

BMC cancer
BACKGROUND: Identifying high risk factors and predicting lung cancer incidence risk are essential to prevention and intervention of lung cancer for the elderly. We aim to develop lung cancer incidence risk prediction model in the elderly to facilitat...

Medical image segmentation based on frequency domain decomposition SVD linear attention.

Scientific reports
Convolutional Neural Networks (CNNs) have achieved remarkable segmentation accuracy in medical image segmentation tasks. However, the Vision Transformer (ViT) model, with its capability of extracting global information, offers a significant advantage...

Eeg Microstates and Balance Parameters for Stroke Discrimination: A Machine Learning Approach.

Brain topography
Electroencephalography microstates (EEG-MS) show promise to be a neurobiological biomarker in stroke. Thus, the aim of the study was to identify biomarkers to discriminate stroke patients from healthy individuals based on EEG-MS and clinical features...

A comparative machine learning study of schizophrenia biomarkers derived from functional connectivity.

Scientific reports
Functional connectivity holds promise as a biomarker of schizophrenia. Yet, the high dimensionality of predictive models trained on functional connectomes, combined with small sample sizes in clinical research, increases the risk of overfitting. Rece...