AIMC Topic: Machine Learning

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AI-Assisted Application for Pediatric Drug Dosing.

Studies in health technology and informatics
Technology in the medical field is continuously advancing due to its numerous subdomains and the ever-growing medical needs of people. Information systems have become integral to doctors' daily routines in patient care, offering flexibility and suppo...

ML-Based Framework to Predict the Severity of the Symptomatology in Patients with Post-Acute COVID-19 Syndrome.

Studies in health technology and informatics
The paper describes a cohort of patients with post-acute COVID-19 syndrome, evaluated for the first time between week 3 and week 12 from the onset of symptoms following the acute COVID-19 infection. The patient's baseline clinical features were used ...

Leveraging Cancer Therapy Peptide Data: A Case Study on Machine Learning Application in Accelerating Cancer Research.

Studies in health technology and informatics
This study leverages the DCTPep database, a comprehensive repository of cancer therapy peptides, to explore the application of machine learning in accelerating cancer research. We applied Principal Component Analysis (PCA) and K-means clustering to c...

Integrating Clinical Data and Patient-Reported Outcomes for Analyzing Gender Differences and Progression in Multiple Sclerosis Using Machine Learning.

Studies in health technology and informatics
Multiple sclerosis (MS) is a complex neurodegenerative disease with a variable prognosis that complicates effective management and treatment. This study leverages machine learning (ML) to enhance the understanding of disease progression and uncover g...

Exploring the Use of AI for Enhanced Accessibility Testing of Web Solutions.

Studies in health technology and informatics
Artificial Intelligence (AI) holds significant potential for enhancing accessibility and user experience across digital products and services. However, mainstream web solutions commonly used by the general population still face accessibility barriers...

Identification and validation of oxidative stress-related genes in primary open-angle glaucoma by weighted gene co-expression network analysis and machine learning.

Medicine
Primary open-angle glaucoma (POAG) is a common ocular disease, and there is currently no effective treatment for POAG therapy. Thus, identifying some effective diagnostic markers is beneficial to the treatment of patients. The expression profile was ...

High-dimensional Immune Profiles and Machine Learning May Predict Acute Myeloid Leukemia Relapse Early following Transplant.

Journal of immunology (Baltimore, Md. : 1950)
Identification of early immune signatures associated with acute myeloid leukemia (AML) relapse following hematopoietic stem cell transplant (HSCT) is critical for patient outcomes. We analyzed PBMCs from 58 patients with AML undergoing HSCT, focusing...

Machine learning-enabled computer vision for plant phenotyping: a primer on AI/ML and a case study on stomatal patterning.

Journal of experimental botany
Artificial intelligence and machine learning (AI/ML) can be used to automatically analyze large image datasets. One valuable application of this approach is estimation of plant trait data contained within images. Here we review 39 papers that describ...

Applications of Machine Learning on Electronic Health Record Data to Combat Antibiotic Resistance.

The Journal of infectious diseases
There is growing excitement about the clinical use of artificial intelligence and machine learning (ML) technologies. Advancements in computing and the accessibility of ML frameworks enable researchers to easily train predictive models using electron...

m6A-related genes and their role in Parkinson's disease: Insights from machine learning and consensus clustering.

Medicine
Parkinson disease (PD) is a chronic neurological disorder primarily characterized by a deficiency of dopamine in the brain. In recent years, numerous studies have highlighted the substantial influence of RNA N6-methyladenosine (m6A) regulators on var...