AIMC Topic: Algorithms

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Identifying individuals at risk for weight gain using machine learning in electronic medical records from the United States.

Diabetes, obesity & metabolism
AIMS: Numerous risk factors for the development of obesity have been identified, yet the aetiology is not well understood. Traditional statistical methods for analysing observational data are limited by the volume and characteristics of large dataset...

Bone-wise rigid registration of femur, tibia, and fibula for the tracking of temporal changes.

Journal of applied clinical medical physics
BACKGROUND: Multiple myeloma (MM) induces temporal alterations in bone structure, such as osteolytic bone lesions, which are challenging to identify through manual image interpretation. The large variation in radiologists' assessments, even at expert...

Ultrafast Hydrogen Detection System Using Vertical Thermal Conduction Structure and Neural Network Prediction Algorithm Based on Sensor Response Process.

ACS sensors
Hydrogen detection plays a crucial role in various scenes of hydrogen energy such as hydrogen vehicles, hydrogen transportation and hydrogen storage. It is essential to develop a hydrogen detection system with ultrafast response times (<1 s) for the ...

Artificial Intelligence Technology Assists Enzyme Prediction and Rational Design.

Journal of agricultural and food chemistry
Since the structure of enzymes determines their function, elucidating the structure of enzymes lays a solid foundation for deciphering their catalytic mechanism and enabling rational design. The development of artificial intelligence (AI) has sparked...

A Novel Explainable Attention-Based Meta-Learning Framework for Imbalanced Brain Stroke Prediction.

Sensors (Basel, Switzerland)
The accurate prediction of brain stroke is critical for effective diagnosis and management, yet the imbalanced nature of medical datasets often hampers the performance of conventional machine learning models. To address this challenge, we propose a n...

PrOsteoporosis: predicting osteoporosis risk using NHANES data and machine learning approach.

BMC research notes
OBJECTIVES: Osteoporosis, prevalent among the elderly population, is primarily diagnosed through bone mineral density (BMD) testing, which has limitations in early detection. This study aims to develop and validate a machine learning approach for ost...

Can some algorithms of machine learning identify osteoporosis patients after training and testing some clinical information about patients?

BMC medical informatics and decision making
OBJECTIVE: This study was designed to establish a diagnostic model for osteoporosis by collecting clinical information from patients with and without osteoporosis. Various machine learning algorithms were employed for training and testing the model, ...

Utilizing SMOTE-TomekLink and machine learning to construct a predictive model for elderly medical and daily care services demand.

Scientific reports
This study aims to construct a prediction model for the demand for medical and daily care services of the elderly and to explore the factors that affect the demand for medical and daily care services of the elderly. In this study, a questionnaire sur...

A machine learning approach to predict mortality and neonatal persistent pulmonary hypertension in newborns with congenital diaphragmatic hernia. A retrospective observational cohort study.

European journal of pediatrics
UNLABELLED: Congenital diaphragmatic hernia (CDH) has high morbidity and mortality rates. This study aimed to develop a machine learning (ML) algorithm to predict outcomes based on prenatal and early postnatal data. This retrospective observational c...

Advancing sepsis diagnosis and immunotherapy machine learning-driven identification of stable molecular biomarkers and therapeutic targets.

Scientific reports
Sepsis represents a significant global health challenge, necessitating early detection and effective treatment for improved outcomes. While traditional inflammatory markers facilitate the diagnosis of sepsis, the aspect of immune suppression remains ...