AIMC Topic: Female

Clear Filters Showing 20801 to 20810 of 29210 articles

Recognition of Sedentary Behavior by Machine Learning Analysis of Wearable Sensors during Activities of Daily Living for Telemedical Assessment of Cardiovascular Risk.

Sensors (Basel, Switzerland)
With the recent advancement in wearable computing, sensor technologies, and data processing approaches, it is possible to develop smart clothing that integrates sensors into garments. The main objective of this study was to develop the method of auto...

Learning to Detect Cognitive Impairment through Digital Games and Machine Learning Techniques.

Methods of information in medicine
OBJECTIVE: Alzheimer's disease (AD) is one of the most prevalent diseases among the adult population. The early detection of Mild Cognitive Impairment (MCI), which may trigger AD, is essential to slow down the cognitive decline process.

SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Breast cancer is the second leading cause of cancer death among women worldwide. Nevertheless, it is also one of the most treatable malignances if detected early. Screening for breast cancer with full field digital mammography (FFDM) has been widely ...

Machine learning ensemble models predict total charges and drivers of cost for transsphenoidal surgery for pituitary tumor.

Journal of neurosurgery
OBJECTIVE: Efficient allocation of resources in the healthcare system enables providers to care for more and needier patients. Identifying drivers of total charges for transsphenoidal surgery (TSS) for pituitary tumors, which are poorly understood, r...

Identifying a neuroanatomical signature of schizophrenia, reproducible across sites and stages, using machine learning with structured sparsity.

Acta psychiatrica Scandinavica
OBJECTIVE: Structural MRI (sMRI) increasingly offers insight into abnormalities inherent to schizophrenia. Previous machine learning applications suggest that individual classification is feasible and reliable and, however, is focused on the predicti...

Improving Prediction of Risk of Hospital Admission in Chronic Obstructive Pulmonary Disease: Application of Machine Learning to Telemonitoring Data.

Journal of medical Internet research
BACKGROUND: Telemonitoring of symptoms and physiological signs has been suggested as a means of early detection of chronic obstructive pulmonary disease (COPD) exacerbations, with a view to instituting timely treatment. However, algorithms to identif...

Robotic Services Acceptance in Smart Environments With Older Adults: User Satisfaction and Acceptability Study.

Journal of medical Internet research
BACKGROUND: In Europe, the population of older people is increasing rapidly. Many older people prefer to remain in their homes but living alone could be a risk for their safety. In this context, robotics and other emerging technologies are increasing...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

Medicina intensiva
INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are intended to be applicable to all patient populations, and generally evaluate in-hospital mortality. Howev...

A Projection Neural Network for Identifying Copy Number Variants.

IEEE journal of biomedical and health informatics
The identification of copy number variations (CNVs) helps the diagnosis of many diseases. One major hurdle in the path of CNVs discovery is that the boundaries of normal and aberrant regions cannot be distinguished from the raw data, since various ty...

Towards End-to-End ECG Classification With Raw Signal Extraction and Deep Neural Networks.

IEEE journal of biomedical and health informatics
This paper proposes deep learning methods with signal alignment that facilitate the end-to-end classification of raw electrocardiogram (ECG) signals into heartbeat types, i.e., normal beat or different types of arrhythmias. Time-domain sample points ...