AIMC Topic: Humans

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Predictive Model to Identify the Long Time Survivor in Patients with Glioblastoma: A Cohort Study Integrating Machine Learning Algorithms.

Journal of molecular neuroscience : MN
We aimed to develop and validate a predictive model for identifying long-term survivors (LTS) among glioblastoma (GB) patients, defined as those with an overall survival (OS) of more than 3 years. A total of 293 GB patients from CGGA and 169 from TCG...

Evaluating seismic risk by MCDM and machine learning for the eastern coast of India.

Environmental monitoring and assessment
Natural disasters such as earthquakes endanger human lives and infrastructure, particularly in urban areas. With the advancements in science and technology in understanding natural hazards, recent studies have attempted to mitigate them by mapping th...

Emergent neural dynamics and geometry for generalization in a transitive inference task.

PLoS computational biology
Relational cognition-the ability to infer relationships that generalize to novel combinations of objects-is fundamental to human and animal intelligence. Despite this importance, it remains unclear how relational cognition is implemented in the brain...

Application of machine learning algorithms to identify people with low bone density.

Frontiers in public health
BACKGROUND: Osteoporosis is becoming more common worldwide, imposing a substantial burden on individuals and society. The onset of osteoporosis is subtle, early detection is challenging, and population-wide screening is infeasible. Thus, there is a n...

Predicting clinical outcomes of SARS-CoV-2 infection during the Omicron wave using machine learning.

PloS one
The Omicron SARS-CoV-2 variant continues to strain healthcare systems. Developing tools that facilitate the identification of patients at highest risk of adverse outcomes is a priority. The study objectives are to develop population-scale predictive ...

Prediction of coronary artery bypass graft outcomes using a single surgical note: An artificial intelligence-based prediction model study.

PloS one
BACKGROUND: Healthcare providers currently calculate risk of the composite outcome of morbidity or mortality associated with a coronary artery bypass grafting (CABG) surgery through manual input of variables into a logistic regression-based risk calc...

The neural network algorithm-based quality assessment method for university English translation.

Network (Bristol, England)
These results highlight the transformative potential of neural network algorithms in providing consistency and transparency while reducing the inherent subjectivity in human evaluations, revolutionizing translation quality assessment in academia. The...

Identification of Age-Related Characteristic Genes Involved in Severe COVID-19 Infection Among Elderly Patients Using Machine Learning and Immune Cell Infiltration Analysis.

Biochemical genetics
Elderly patients infected with severe acute respiratory syndrome coronavirus 2 are at higher risk of severe clinical manifestation, extended hospitalization, and increased mortality. Those patients are more likely to experience persistent symptoms an...

A systematic review of prediction models on arteriovenous fistula: Risk scores and machine learning approaches.

The journal of vascular access
OBJECTIVE: Failure-to-mature and early stenosis remains the Achille's heel of hemodialysis arteriovenous fistula (AVF) creation. The maturation and patency of an AVF can be influenced by a variety of demographic, comorbidity, and anatomical factors. ...

A deep learning-based calculation system for plaque stenosis severity on common carotid artery of ultrasound images.

Vascular
ObjectivesAssessment of plaque stenosis severity allows better management of carotid source of stroke. Our objective is to create a deep learning (DL) model to segment carotid intima-media thickness and plaque and further automatically calculate plaq...