AIMC Topic: Severity of Illness Index
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Motor assessment of X-linked dystonia parkinsonism via machine-learning-based analysis of wearable sensor data.
Scientific reports
Jun 9, 2024
X-linked dystonia parkinsonism (XDP) is a neurogenetic combined movement disorder involving both parkinsonism and dystonia. Complex, overlapping phenotypes result in difficulties in clinical rating scale assessment. We performed wearable sensor-based...
Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.
Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
Jun 8, 2024
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...
Automatic evaluation of Nail Psoriasis Severity Index using deep learning algorithm.
The Journal of dermatology
Jun 7, 2024
Nail psoriasis is a chronic condition characterized by nail dystrophy affecting the nail matrix and bed. The severity of nail psoriasis is commonly assessed using the Nail Psoriasis Severity Index (NAPSI), which evaluates the characteristics and exte...
Feature group partitioning: an approach for depression severity prediction with class balancing using machine learning algorithms.
BMC medical research methodology
Jun 3, 2024
In contemporary society, depression has emerged as a prominent mental disorder that exhibits exponential growth and exerts a substantial influence on premature mortality. Although numerous research applied machine learning methods to forecast signs o...
Early prediction of acute gallstone pancreatitis severity: a novel machine learning model based on CT features and open access online prediction platform.
Annals of medicine
May 30, 2024
BACKGROUND: Early diagnosis of acute gallstone pancreatitis severity (GSP) is challenging in clinical practice. We aimed to investigate the efficacy of CT features and radiomics for the early prediction of acute GSP severity.
Metabolic profiling during COVID-19 infection in humans: Identification of potential biomarkers for occurrence, severity and outcomes using machine learning.
PloS one
May 30, 2024
BACKGROUND: After its emergence in China, the coronavirus SARS-CoV-2 has swept the world, leading to global health crises with millions of deaths. COVID-19 clinical manifestations differ in severity, ranging from mild symptoms to severe disease. Alth...
Towards a machine-learning assisted non-invasive classification of dengue severity using wearable PPG data: a prospective clinical study.
EBioMedicine
May 29, 2024
BACKGROUND: Dengue epidemics impose considerable strain on healthcare resources. Real-time continuous and non-invasive monitoring of patients admitted to the hospital could lead to improved care and outcomes. We evaluated the performance of a commerc...
Prediction of inhibitor development in previously untreated and minimally treated children with severe and moderately severe hemophilia A using a machine-learning network.
Journal of thrombosis and haemostasis : JTH
May 27, 2024
BACKGROUND: Prediction of inhibitor development in patients with hemophilia A (HA) remains a challenge.
An Artificial Neural Network Predicts Gender Differences of Motor and Non-Motor Symptoms of Patients with Advanced Parkinson's Disease under Levodopa-Carbidopa Intestinal Gel.
Medicina (Kaunas, Lithuania)
May 26, 2024
: Currently, no tool exists to predict clinical outcomes in patients with advanced Parkinson's disease (PD) under levodopa-carbidopa intestinal gel (LCIG) treatment. The aim of this study was to develop a novel deep neural network model to predict th...
Deep learning reveals lung shape differences on baseline chest CT between mild and severe COVID-19: A multi-site retrospective study.
Computers in biology and medicine
May 23, 2024
Severe COVID-19 can lead to extensive lung disease causing lung architectural distortion. In this study we employed machine learning and statistical atlas-based approaches to explore possible changes in lung shape among COVID-19 patients and evaluate...
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