AIMC Topic: Machine Learning

Clear Filters Showing 14831 to 14840 of 34417 articles

Identification of hospitalized mortality of patients with COVID-19 by machine learning models based on blood inflammatory cytokines.

Frontiers in public health
Coronavirus disease 2019 (COVID-19) spread worldwide and presented a significant threat to people's health. Inappropriate disease assessment and treatment strategies bring a heavy burden on healthcare systems. Our study aimed to construct predictive ...

Tracking financing for global common goods for health: A machine learning approach using natural language processing techniques.

Frontiers in public health
OBJECTIVE: Tracking global health funding is a crucial but time consuming and labor-intensive process. This study aimed to develop a framework to automate the tracking of global health spending using natural language processing (NLP) and machine lear...

Application of machine learning techniques to the analysis and prediction of drug pharmacokinetics.

Journal of controlled release : official journal of the Controlled Release Society
In this review, we describe the current status and challenges in applying machine-learning techniques to the analysis and prediction of pharmacokinetic data. The theory of pharmacokinetics has been developed over decades on the basis of physiology an...

Prediction of monthly dry days with machine learning algorithms: a case study in Northern Bangladesh.

Scientific reports
Dry days at varied scale are an important topic in climate discussions. Prolonged dry days define a dry period. Dry days with a specific rainfall threshold may visualize a climate scenario of a locality. The variation of monthly dry days from station...

Personalized prediction of optimal water intake in adult population by blended use of machine learning and clinical data.

Scientific reports
Growing evidence suggests that sustained concentrated urine contributes to chronic metabolic and kidney diseases. Recent results indicate that a daily urinary concentration of 500 mOsm/kg reflects optimal hydration. This study aims at providing perso...

Evaluation of word embedding models to extract and predict surgical data in breast cancer.

BMC bioinformatics
BACKGROUND: Decisions in healthcare usually rely on the goodness and completeness of data that could be coupled with heuristics to improve the decision process itself. However, this is often an incomplete process. Structured interviews denominated De...

Prediction of gender from longitudinal MRI data via deep learning on adolescent data reveals unique patterns associated with brain structure and change over a two-year period.

Journal of neuroscience methods
Deep learning algorithms for predicting neuroimaging data have shown considerable promise in various applications. Prior work has demonstrated that deep learning models that take advantage of the data's 3D structure can outperform standard machine le...

Utilizing artificial intelligence and electroencephalography to assess expertise on a simulated neurosurgical task.

Computers in biology and medicine
Virtual reality surgical simulators have facilitated surgical education by providing a safe training environment. Electroencephalography (EEG) has been employed to assess neuroelectric activity during surgical performance. Machine learning (ML) has b...

Software for segmenting and quantifying calcium signals using multi-scale generative adversarial networks.

STAR protocols
Cellular calcium fluorescence imaging utilized to study cellular behaviors typically results in large datasets and a profound need for standardized and accurate analysis methods. Here, we describe open-source software (4SM) to overcome these limitati...