AIMC Topic: Female

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Machine learning models for outcome prediction in thrombectomy for large anterior vessel occlusion.

Annals of clinical and translational neurology
OBJECTIVE: Predicting long-term functional outcomes shortly after a stroke is challenging, even for experienced neurologists. Therefore, we aimed to evaluate multiple machine learning models and the importance of clinical/radiological parameters to d...

Metabolomics Unveils Disrupted Pathways in Parkinson's Disease: Toward Biomarker-Based Diagnosis.

ACS chemical neuroscience
Parkinson's disease (PD) is a neurodegenerative disorder characterized by diverse symptoms, where accurate diagnosis remains challenging. Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biomarker-based...

Predicting high blood pressure using machine learning models in low- and middle-income countries.

BMC medical informatics and decision making
Responding to the rising global prevalence of noncommunicable diseases (NCDs) requires improvements in the management of high blood pressure. Therefore, this study aims to develop an explainable machine learning model for predicting high blood pressu...

Risk factors for the time to development of retinopathy of prematurity in premature infants in Iran: a machine learning approach.

BMC ophthalmology
BACKGROUND: Retinopathy of prematurity (ROP), is a preventable leading cause of blindness in infants and is a condition in which the immature retina experiences abnormal blood vessel growth. The development of ROP is multifactorial; nevertheless, the...

Factors for increasing positive predictive value of pneumothorax detection on chest radiographs using artificial intelligence.

Scientific reports
This study evaluated the positive predictive value (PPV) of artificial intelligence (AI) in detecting pneumothorax on chest radiographs (CXRs) and its affecting factors. Patients determined to have pneumothorax on CXR by a commercial AI software from...

Evaluation of perceived urgency from single-trial EEG data elicited by upper-body vibration feedback using deep learning.

Scientific reports
Notification systems that convey urgency without adding cognitive burden are crucial in human-computer interaction. Haptic feedback systems, particularly those utilizing vibration feedback, have emerged as a compelling solution, capable of providing ...

Improving the Social Well-Being of Single Older Adults Using the LOVOT Social Robot: Qualitative Phenomenological Study.

JMIR human factors
BACKGROUND: This study examined the social well-being of single older adults through the companionship of a social robot, LOVOT (Love+Robot; Groove X). It is designed as a companion for older adults, providing love and affection through verbal and ph...

Sexually dimorphic computational histopathological signatures prognostic of overall survival in high-grade gliomas via deep learning.

Science advances
High-grade glioma (HGG) is an aggressive brain tumor. Sex is an important factor that differentially affects survival outcomes in HGG. We used an end-to-end deep learning approach on hematoxylin and eosin (H&E) scans to (i) identify sex-specific hist...

Simultaneous EEG-fNIRS Data Classification Through Selective Channel Representation and Spectrogram Imaging.

IEEE journal of translational engineering in health and medicine
The integration of electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) can facilitate the advancement of brain-computer interfaces (BCIs). However, existing research in this domain has grappled with the challenge of the eff...