AIMC Topic: Machine Learning

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A machine learning approach to identify patients at risk for long-term consequences after pulmonary embolism.

Scientific reports
Pulmonary embolism (PE) can result in long-term sequelae, such as post-PE syndrome, including persistent dyspnea and chronic thromboembolic pulmonary hypertension (CTEPH). Existing prediction tools for severe post-PE complications lack sensitivity an...

Machine learning comparison for biomarker level estimation in wastewater dynamics monitoring.

Scientific reports
Wastewater surveillance is an emerging strategy that enables monitoring of the presence and dynamic changes of targeted substances, facilitating improved allocation of preventive actions and public health interventions. This paper investigates the ap...

Deep fusion based transfer learning with bald eagle search algorithm for sign language recognition to assist individuals with hearing and speech impairments.

Scientific reports
Sign language (SL) is a significant communication method for individuals with hearing impairments, using hand gestures to convey letters, words, and sentences. However, several people are unfamiliar with SL, creating a communication gap. An intellige...

Structure based drug design and machine learning approaches for identifying natural inhibitors against the human αβIII tubulin isotype.

Scientific reports
Microtubules (MTs) play a crucial role in mitosis and are composed of α-/β-tubulin heterodimeric subunits. In eukaryotes, eight α-tubulin and ten β-tubulin isotypes have been reported, each displaying tissue-specific expression patterns. Among them, ...

Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.

NPJ systems biology and applications
Physical inactivity and low fitness have become global health concerns. Metabolomics, as an integrative approach, may link fitness to molecular changes. In this study, we analyzed blood metabolomes from elderly individuals under different treatments....

Diabetic Foot Ulcer Classification Models Using Artificial Intelligence and Machine Learning Techniques: Systematic Review.

Journal of medical Internet research
BACKGROUND: Diabetes-related foot ulceration (DFU) is a common complication of diabetes, with a significant impact on survival, health care costs, and health-related quality of life. The prognosis of DFU varies widely among individuals. The Internati...

Machine Learning in Health Economic Evaluations: Protocol for a Scoping Review.

JMIR research protocols
BACKGROUND: In recent years, the development of machine learning (ML) applications has increased substantially, indicating the potential role of ML in transforming health care. However, the integration of ML approaches into health economic evaluation...

Interpretable Machine Learning Model for Pulmonary Hypertension Risk Prediction: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Pulmonary hypertension (PH) is a progressive disorder characterized by elevated pulmonary artery pressure and increased pulmonary vascular resistance, ultimately leading to right heart failure. Early detection is critical for improving pa...

Early clinical evaluation of a machine-learning system for risk prediction of trauma-induced coagulopathy in the prehospital setting.

Emergency medicine journal : EMJ
BACKGROUND: Early intervention in patients with major traumatic injuries is critical. Decision support can improve clinicians' ability to identify high-risk patients. The aim of this study was to compare the performance of a machine-learning (ML) dec...

Prediction of biological age using machine learning.

PloS one
In response to Taiwan's rapidly aging population and the rising demand for personalized health care, accurately assessing individual physiological aging has become an essential area of study. This research utilizes health examination data to propose ...