AIMC Topic: Aged

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XGBoost Model for Chronic Kidney Disease Diagnosis.

IEEE/ACM transactions on computational biology and bioinformatics
Chronic Kidney Disease (CKD) is a menace that is affecting 10 percent of the world population and 15 percent of the South African population. The early and cheap diagnosis of this disease with accuracy and reliability will save 20,000 lives in South ...

[Robot-Assisted Right Hemihepatectomy for Hepatocellular Carcinoma].

Zentralblatt fur Chirurgie
Since the introduction of robot-assisted surgery, increasingly complex operations have been performed with this technique. Robot-assisted operations are also of increasing importance in hepatobiliary surgery. With articulated and scaled movements in ...

Exploring dyserythropoiesis in patients with myelodysplastic syndrome by imaging flow cytometry and machine-learning assisted morphometrics.

Cytometry. Part B, Clinical cytometry
BACKGROUND: The hallmark of myelodysplastic syndrome (MDS) remains dysplasia in the bone marrow (BM). However, diagnosing MDS may be challenging and subject to inter-observer variability. Thus, there is an unmet need for novel objective, standardized...

Estimating the health-related quality of life of kidney stone patients: initial results from the Wisconsin Stone Quality of Life Machine-Learning Algorithm (WISQOL-MLA).

BJU international
OBJECTIVE: To build the Wisconsin Stone Quality of Life Machine-Learning Algorithm (WISQOL-MLA) to predict urolithiasis patients' health-related quality of life (HRQoL) based on demographic, symptomatic and clinical data collected for the validation ...

A Process Evaluation Examining the Performance, Adherence, and Acceptability of a Physical Activity and Diet Artificial Intelligence Virtual Health Assistant.

International journal of environmental research and public health
Artificial intelligence virtual health assistants are a promising emerging technology. This study is a process evaluation of a 12-week pilot physical activity and diet program delivered by virtual assistant "Paola". This single-arm repeated measures ...

A Robust Feature Extraction Model for Human Activity Characterization Using 3-Axis Accelerometer and Gyroscope Data.

Sensors (Basel, Switzerland)
Human Activity Recognition (HAR) using embedded sensors in smartphones and smartwatch has gained popularity in extensive applications in health care monitoring of elderly people, security purpose, robotics, monitoring employees in the industry, and o...

Identification of Sleep Apnea Severity Based on Deep Learning from a Short-term Normal ECG.

Journal of Korean medical science
BACKGROUND: This paper proposes a novel method for automatically identifying sleep apnea (SA) severity based on deep learning from a short-term normal electrocardiography (ECG) signal.

Unobtrusive detection of Parkinson's disease from multi-modal and in-the-wild sensor data using deep learning techniques.

Scientific reports
Parkinson's Disease (PD) is the second most common neurodegenerative disorder, affecting more than 1% of the population above 60 years old with both motor and non-motor symptoms of escalating severity as it progresses. Since it cannot be cured, treat...

Deep learning to diagnose cardiac amyloidosis from cardiovascular magnetic resonance.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Cardiovascular magnetic resonance (CMR) is part of the diagnostic work-up for cardiac amyloidosis (CA). Deep learning (DL) is an application of artificial intelligence that may allow to automatically analyze CMR findings and establish the...