AIMC Topic: Humans

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Energy-Efficient Intelligent ECG Monitoring for Wearable Devices.

IEEE transactions on biomedical circuits and systems
Wearable intelligent ECG monitoring devices can perform automatic ECG diagnosis in real time and send out alert signal together with abnormal ECG signal for doctor's further analysis. This provides a means for the patient to identify their heart prob...

Validation of computerized square-drawing based evaluation of motor function in patients with stroke.

Medical engineering & physics
Human-administered clinical scales are commonly used for quantifying motor performance and determining the course of therapy in post-stroke individuals. Computerized methods aim to improve consistency, resolution and duration of patients' evaluation....

An artificial intelligence-based clinical decision support system for large kidney stone treatment.

Australasian physical & engineering sciences in medicine
A decision support system (DSS) was developed to predict postoperative outcome of a kidney stone treatment procedure, particularly percutaneous nephrolithotomy (PCNL). The system can serve as a promising tool to provide counseling before an operation...

Robot-Assisted Arm Training in Chronic Stroke: Addition of Transition-to-Task Practice.

Neurorehabilitation and neural repair
. Robot-assisted therapy provides high-intensity arm rehabilitation that can significantly reduce stroke-related upper extremity (UE) deficits. Motor improvement has been shown at the joints trained, but generalization to real-world function has not ...

Phenotyping Women Based on Dietary Macronutrients, Physical Activity, and Body Weight Using Machine Learning Tools.

Nutrients
Nutritional phenotyping can help achieve personalized nutrition, and machine learning tools may offer novel means to achieve phenotyping. The primary aim of this study was to use energy balance components, namely input (dietary energy intake and macr...

Targeting HIV/HCV Coinfection Using a Machine Learning-Based Multiple Quantitative Structure-Activity Relationships (Multiple QSAR) Method.

International journal of molecular sciences
Human immunodeficiency virus type-1 and hepatitis C virus (HIV/HCV) coinfection occurs when a patient is simultaneously infected with both human immunodeficiency virus type-1 (HIV-1) and hepatitis C virus (HCV), which is common today in certain popul...

Identification of Patients in Need of Advanced Care for Depression Using Data Extracted From a Statewide Health Information Exchange: A Machine Learning Approach.

Journal of medical Internet research
BACKGROUND: As the most commonly occurring form of mental illness worldwide, depression poses significant health and economic burdens to both the individual and community. Different types of depression pose different levels of risk. Individuals who s...

Development and validation of a pragmatic natural language processing approach to identifying falls in older adults in the emergency department.

BMC medical informatics and decision making
BACKGROUND: Falls among older adults are both a common reason for presentation to the emergency department, and a major source of morbidity and mortality. It is critical to identify fall patients quickly and reliably during, and immediately after, em...

Characterization of clinical patterns of dengue patients using an unsupervised machine learning approach.

BMC infectious diseases
BACKGROUND: Despite the greater sensitivity of the new dengue clinical classification proposed by the World Health Organization (WHO) in 2009, there is a need for a better definition of warning signs and clinical progression of dengue cases. Classic ...

Chemical-induced disease relation extraction via attention-based distant supervision.

BMC bioinformatics
BACKGROUND: Automatically understanding chemical-disease relations (CDRs) is crucial in various areas of biomedical research and health care. Supervised machine learning provides a feasible solution to automatically extract relations between biomedic...