AIMC Topic: Humans

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Is artificial intelligence superior to traditional regression methods in predicting prognosis of adult traumatic brain injury?

Neurosurgical review
Traumatic brain injury (TBI) is a significant global health issue with high morbidity and mortality rates. Recent studies have shown that machine learning algorithms outperform traditional logistic regression models in predicting functional outcomes ...

Evaluation of machine learning methods for prediction of heart failure mortality and readmission: meta-analysis.

BMC cardiovascular disorders
BACKGROUND: Heart failure (HF) impacts nearly 6 million individuals in the U.S., with a projected 46% increase by 2030, is creating significant healthcare burdens. Predictive models, particularly machine learning (ML)-based models, offer promising so...

ECG-based heart arrhythmia classification using feature engineering and a hybrid stacked machine learning.

BMC cardiovascular disorders
A heart arrhythmia refers to a set of conditions characterized by irregular heart- beats, with an increasing mortality rate in recent years. Regular monitoring is essential for effective management, as early detection and timely treatment greatly imp...

Prediction of Seronegative Hashimoto's thyroiditis using machine learning models based on ultrasound radiomics: a multicenter study.

BMC immunology
BACKGROUND: Seronegative Hashimoto's thyroiditis is often underdiagnosed due to the lack of antibody markers. Combining ultrasound radiomics with machine learning offers potential for early detection in patients with normal thyroid function.

DP-MP: a novel cross-subject fatigue detection framework with DANN-based prototypical representation and mix-up pairwise learning.

Journal of neural engineering
. Electroencephalography (EEG) is widely recognized as an effective method for detecting fatigue. However, practical applications of EEG for fatigue detection in real-world scenarios are often challenging, particularly in cases involving subjects not...

The Future of Scientific Writing: AI Tools, Benefits, and Ethical Implications.

Brazilian dental journal
Artificial Intelligence (AI) transforms scientific writing by improving efficiency, accessibility, and quality. This study evaluated the applications, benefits, and challenges of AI tools, including Elicit, Perplexity, Consensus, ChatGPT, and Grammar...

Ensemble deep learning for Alzheimer's disease diagnosis using MRI: Integrating features from VGG16, MobileNet, and InceptionResNetV2 models.

PloS one
Alzheimer's disease (AD) is a neurodegenerative disorder characterized by the accumulation of amyloid plaques and neurofibrillary tangles in the brain, leading to distinctive patterns of neuronal dysfunction and the cognitive decline emblematic of de...

Classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing.

PloS one
In order to accurately assess the students' learning process and the cognitive state of knowledge points in smart classroom. A classroom network structure learning engagement and parallel temporal attention LSTM based knowledge tracing model (CL-PTKT...

CNN-LSTM based emotion recognition using Chebyshev moment and K-fold validation with multi-library SVM.

PloS one
Human emotions are not necessarily tends to produce right facial expressions as there is no well defined connection between them. Although, human emotions are spontaneous, their facial expressions depend a lot on their mental and psychological capaci...

Gut microbiota shift in Ghanaian individuals along the migration axis: the RODAM-Pros cohort.

Gut microbes
Migration is associated with a substantial change in environmental exposures and health outcomes. We aimed to investigate the shift in gut microbiota composition and the associations with cardiometabolic outcomes in the RODAM-Pros cohort spanning mul...