AIMC Topic: Potassium
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Application of causal forests to randomised controlled trial data to identify heterogeneous treatment effects: a case study.
BMC medical research methodology
Feb 22, 2025
BACKGROUND: Classical approaches to subgroup analysis in randomised controlled trials (RCTs) to identify heterogeneous treatment effects (HTEs) involve testing the interaction between each pre-specified possible treatment effect modifier and the trea...
Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Feb 18, 2025
This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWI...
Nutrient based classification of Phyllospora comosa biomasses using machine learning algorithms: Towards sustainable valorisation.
Food research international (Ottawa, Ont.)
Dec 31, 2024
Sustainable seaweed value chains necessitate accurate biomass biochemical characterisation that leads to product development, geographical authentications and quality and sustainability assurances. Underutilised yet abundantly available seaweed speci...
Serum Potassium Monitoring Using AI-Enabled Smartwatch Electrocardiograms.
JACC. Clinical electrophysiology
Oct 9, 2024
BACKGROUND: Hyperkalemia, characterized by elevated serum potassium levels, heightens the risk of sudden cardiac death, particularly increasing risk for individuals with chronic kidney disease and end-stage renal disease (ESRD). Traditional laborator...
Risk prediction of kalaemia disturbance and acute kidney injury after total knee arthroplasty: use of a machine learning algorithm.
Orthopaedics & traumatology, surgery & research : OTSR
Jul 22, 2024
INTRODUCTION: Total knee arthroplasty (TKA) is a procedure associated with risks of electrolyte and kidney function disorders, which are rare but can lead to serious complications if not correctly identified. A routine check-up is very often carried ...
Synergistic Machine Learning Accelerated Discovery of Nanoporous Inorganic Crystals as Non-Absorbable Oral Drugs.
Advanced materials (Deerfield Beach, Fla.)
Jun 6, 2024
Machine learning (ML) has taken drug discovery to new heights, where effective ML training requires vast quantities of high-quality experimental data as input. Non-absorbable oral drugs (NODs) have unique safety advantage for chronic diseases due to ...
Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer's Disease Using Biophysical Modeling and Deep Learning.
Bulletin of mathematical biology
Mar 25, 2024
Alzheimer's disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopathy or tauopa...
Severe Hyperkalemia During a Robot-Assisted Total Radical Prostatectomy in a Patient with Stage 3a Chronic Kidney Disease: A Case Report.
A&A practice
Feb 27, 2024
A 63-year-old man with stage 3a chronic kidney disease (CKD) and mild hyperkalemia was scheduled for a robot-assisted prostatectomy. He was being treated with lisinopril. Owing to mild hyperkalemia (6.2 mmol/L), lisinopril was discontinued, and sodiu...
Effectiveness of continuity of care after robot-assisted laparoscopic adrenalectomy under ambulatory mode: a single-center intervention study.
Journal of robotic surgery
Jan 11, 2024
To investigate the effectiveness of continuity of care after robot-assisted adrenal tumor resection under ambulatory mode. Patients who underwent robot-assisted laparoscopic adrenalectomy (RALA) in the ambulatory surgery department and urology depart...
Association between household income levels and nutritional intake of allergic children under 6 years of age in Korea: 2019 Korea National Health and Nutrition Examination Survey and application of machine learning.
Frontiers in public health
Jan 8, 2024
INTRODUCTION: This study investigated the prevalence of allergic diseases in Korean children aged 6 and below, focusing on the interplay between nutritional status, household income levels, and allergic disease occurrence.
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