AIMC Topic: Machine Learning

Clear Filters Showing 901 to 910 of 32557 articles

Cervical cancer prediction using machine learning models based on routine blood analysis.

Scientific reports
Cervical cancer (CC) is the fourth most common cancer among women globally. The key to preventing and treating CC is early detection, diagnosis, and treatment. This study aimed to develop an interpretable model for predicting CC risk using routine bl...

Machine learning model and hemoglobin to red cell distribution width ratio evaluates all-cause mortality in pulmonary embolism.

Scientific reports
The ratio of hemoglobin (Hb) to red blood cell distribution width (RDW), known as HRR, functions as an innovative indicator related to prognosis. However, whether HRR can predict the mortality for pulmonary embolism (PE) patients remains ambiguous. A...

The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms.

Scientific reports
Hematoporphyrin monomethyl ether-photodynamic therapy (HMME-PDT) is a safe and effective treatment for port-wine stain (PWS). Comprehensive methods for predicting HMME-PDT efficacy based on clinical factors are lacking. This study aims to develop and...

Advanced machine learning applications in fibromyalgia to assess the relationship between 3D spinal alignment with clinical outcomes.

Scientific reports
This study leveraged machine learning (ML) models to explore the relationship between three-dimensional (3D) spinal alignment parameters and clinical outcomes in patients suffering from fibromyalgia syndrome (FMS). A cohort of 303 FMS patients, diagn...

Using graph machine learning to identify functioning in patients with low back pain in terms of ICF.

Scientific reports
As a comprehensive perspective on functioning is useful in patient assessments, the WHO developed the International Classification of Functioning, Disability, and Health (ICF) to provide a standardized terminology and framework for describing and cla...

Recognition of anxiety and depression using gait data recorded by the kinect sensor: a machine learning approach with data augmentation.

Scientific reports
Anxiety and depression disorders are increasingly common, necessitating methods for real-time assessment and early identification. This study investigates gait analysis as a potential indicator of mental health, using the Microsoft Kinect sensor to c...

Implementing partial least squares and machine learning regressive models for prediction of drug release in targeted drug delivery application.

Scientific reports
A combined methodology was performed based on chemometrics and machine learning regressive models in estimation of polysaccharide-coated colonic drug delivery. The release of medication was measured using Raman spectroscopy and the data was used for ...

Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging.

Scientific reports
Early diagnosis of Neurological Disorders (ND) such as Alzheimer's disease (AD) and Brain Tumors (BT) can be highly challenging since these diseases cause minor changes in the brain's anatomy. Magnetic Resonance Imaging (MRI) is a vital tool for diag...

A multi-modal graph-based framework for Alzheimer's disease detection.

Scientific reports
We propose a compositional graph-based Machine Learning (ML) framework for Alzheimer's disease (AD) detection that constructs complex ML predictors from modular components. In our directed computational graph, datasets are represented as nodes [Formu...

Comparative study of five-year cervical cancer cause-specific survival prediction models based on SEER data.

Scientific reports
Cervical cancer (CC) is a major cause of mortality in women, with stagnant survival rates, highlighting the need for improved prognostic models. This study aims to develop and compare machine learning models for predicting five-year cause-specific su...