AIMC Topic: Female

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Steady-state neuron-predominant LINE-1 encoded ORF1p protein and LINE-1 RNA increase with aging in the mouse and human brain.

eLife
Recent studies have established a reciprocal causal link between aging and the activation of transposable elements, characterized in particular by a de-repression of LINE-1 retrotransposons. These LINE-1 elements represent 21% of the human genome, bu...

EEG Microstates Signatures of rTMS Response Over the lDLPFC: A Band-Specific Analysis.

Brain topography
Transcranial Magnetic Stimulation (TMS), particularly Theta Burst Stimulation (TBS), is a non-invasive, non-convulsive neuromodulation technique that induces clinically relevant network modulations with long-term effects. Two TBS protocols- continuou...

Predicting postoperative fever in culture-negative patients undergoing mini-PCNL using MAP score-augmented machine learning: a retrospective cohort study.

World journal of urology
PURPOSE: Postoperative fever is a common complication following percutaneous nephrolithotomy (PCNL) that occurs even in patients with sterile urine cultures. Traditional risk-assessment tools are insufficient in this subset of patients. This study ai...

Machine Learning-Based Classification of White Matter Functional Changes in Stroke Patients Using Resting-State fMRI.

Brain topography
Neuroimaging studies of brain function are important research methods widely applied to stroke patients. Currently, a large number of studies have focused on functional imaging of the gray matter cortex. Relevant research indicates that certain areas...

Clinical Performance Evaluation of an Artificial Intelligence-Based Tool for Predicting the Presence of Obstructive Coronary Artery Disease: Protocol for a Cohort Observational Study.

JMIR research protocols
BACKGROUND: A significant number of individuals undergoing coronary computed tomography angiography (CCTA) for suspected (CAD) have nonobstructive or no CAD. There is a need for clinically proven models that can predict the pretest probability of sta...

CNN-based prediction using early post-radiotherapy MRI as a proxy for toxicity in the murine head and neck.

Acta oncologica (Stockholm, Sweden)
BACKGROUND AND PURPOSE: Radiotherapy (RT) of head and neck cancer can cause severe toxicities. Early identification of individuals at risk could enable personalized treatment. This study evaluated whether convolutional neural networks (CNNs) applied ...

Introduction of sub-band augmentation with machine learning to develop an insomnia classification model using single-channel EEG signals.

Physiological measurement
. Biological signals can be used to record sleep activities and can be used to identify sleep disorders. Insomnia is a sleep disorder that can be detected using supervised learning models developed using biological signal analysis. The baseline insom...

Equitable AI: Exploring the role of gender in poverty estimation models using geospatial data.

PloS one
Household surveys have been the foundation for poverty measurement in developing countries for the past half-century, but the spatial and temporal gaps in these survey data often limit how well anti-poverty programs can be targeted, monitored, or eva...

Latent representation of H&E images retains biological information in a breast cancer cohort.

PloS one
Imaging technologies and staining based pathology are important components of common practice cancer care. Specifically, H&E imaging is standard for almost all cancer patients. Traditionally, H&E images can serve, when used by experienced trained pat...

Evaluating the diagnostic performance of OpenBioLLM in neurology: A case-based assessment of a medical large language model.

PloS one
In the evolving field of neurological healthcare, deep learning technologies are gaining recognition for their potential to enhance diagnostic accuracy. Transformer-based models, particularly large language models (LLMs) such as OpenBioLLM, have show...