Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9353984 | PMC |
| http://dx.doi.org/10.1089/bio.2021.29089.mwv | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Pain can't be carved at the joints: defining function-based pain profiles and their relevance to chronic disease management in healthcare delivery design.
BMC Med
December 2024
Department of Biomedical Engineering, Montreal Neurological Institute, McGill University and Mila - Quebec AI Institute, Montreal, Canada.
Background: Pain is a complex problem that is triaged, diagnosed, treated, and billed based on which body part is painful, almost without exception. While the "body part framework" guides the organization and treatment of individual patients' pain conditions, it remains unclear how to best conceptualize, study, and treat pain conditions at the population level. Here, we investigate (1) how the body part framework agrees with population-level, biologically derived pain profiles; (2) how do data-derived pain profiles interface with other symptom domains from a whole-body perspective; and (3) whether biologically derived pain profiles capture clinically salient differences in medical history.
View Article and Find Full Text PDFEmerging Biomarkers in Metabolomics: Advancements in Precision Health and Disease Diagnosis.
Int J Mol Sci
December 2024
BioNano Applications Research Center, Gachon University, 1342 Seongnam-daero, Sujeong-gu, Seongnam-si 13120, Gyeonggi-do, Republic of Korea.
Metabolomics has come to the fore as an efficient tool in the search for biomarkers that are critical for precision health approaches and improved diagnostics. This review will outline recent advances in biomarker discovery based on metabolomics, focusing on metabolomics biomarkers reported in cancer, neurodegenerative disorders, cardiovascular diseases, and metabolic health. In cancer, metabolomics provides evidence for unique oncometabolites that are important for early disease detection and monitoring of treatment responses.
View Article and Find Full Text PDFSculpting Success: The Importance of Diet and Physical Activity to Support Skeletal Muscle Health during Weight Loss with New Generation Anti-Obesity Medications.
Curr Dev Nutr
November 2024
Department of Scientific and Clinical Affairs, Medifast, Inc, Baltimore, MD, United States.
Obesity is a public health crisis, with prevalence rates tripling over the past 60 y. Although lifestyle modifications, such as diet and physical activity, remain the first-line treatments, recent anti-obesity medications (AOMs) have been shown to achieve greater reductions in body weight and fat mass. However, AOMs also reduce fat-free mass, including skeletal muscle, which has been demonstrated to account for 20% to 50% of total weight loss.
View Article and Find Full Text PDFContributing to the prediction of prognosis for treated hepatocellular carcinoma: Imaging aspects that sculpt the future.
World J Gastrointest Surg
October 2024
Department of Radiology, Faculty of Medicine, University of Concepcion, Concepcion 4030000, Biobío, Chile.
A novel nomogram model to predict the prognosis of hepatocellular carcinoma (HCC) treated with radiofrequency ablation and transarterial chemoembolization was recently published in the . This model includes clinical and laboratory factors, but emerging imaging aspects, particularly from magnetic resonance imaging (MRI) and radiomics, could enhance the predictive accuracy thereof. Multiparametric MRI and deep learning radiomics models significantly improve prognostic predictions for the treatment of HCC.
View Article and Find Full Text PDFPioneering Klebsiella Pneumoniae Antibiotic Resistance Prediction With Artificial Intelligence-Clinical Decision Support System-Enhanced Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry: Retrospective Study.
J Med Internet Res
November 2024
Division of Clinical Pathology, Department of Pathology, Tri-Service General Hospital, National Defense Medical Center, Taipei City, Taiwan.
Background: The rising prevalence and swift spread of multidrug-resistant gram-negative bacteria (MDR-GNB), especially Klebsiella pneumoniae (KP), present a critical global health threat highlighted by the World Health Organization, with mortality rates soaring approximately 50% with inappropriate antimicrobial treatment.
Objective: This study aims to advance a novel strategy to develop an artificial intelligence-clinical decision support system (AI-CDSS) that combines machine learning (ML) with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS), aiming to significantly improve the accuracy and speed of diagnosing antibiotic resistance, directly addressing the grave health risks posed by the widespread dissemination of pan drug-resistant gram-negative bacteria across numerous countries.
Methods: A comprehensive dataset comprising 165,299 bacterial specimens and 11,996 KP isolates was meticulously analyzed using MALDI-TOF MS technology.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!