AIMC Topic: Hemoglobins

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Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy.

Communications biology
Translation of the findings in basic science and clinical research into routine practice is hampered by large variations in human phenotype. Developments in genotyping and phenotyping, such as proteomics and lipidomics, are beginning to address these...

Regular cold water swimming during winter time affects resting hematological parameters and serum erythropoietin.

Journal of physiology and pharmacology : an official journal of the Polish Physiological Society
Recreational winter swimming in cold sea water evokes body responses to regularly repeated cold water immersion. However, the understanding of adaptive changes is still limited and data regarding very short-term exposure to severe cold stress are sca...

Machine learning as new promising technique for selection of significant features in obese women with type 2 diabetes.

Hormone molecular biology and clinical investigation
Background The global trend of obesity and diabetes is considerable. Recently, the early diagnosis and accurate prediction of type 2 diabetes mellitus (T2DM) patients have been planned to be estimated according to precise and reliable methods, artifi...

Non-Invasive Estimation of Hemoglobin Using a Multi-Model Stacking Regressor.

IEEE journal of biomedical and health informatics
OBJECTIVE: We describe a novel machine-learning based method to estimate total Hemoglobin (Hb) using photoplethysmograms (PPGs) acquired non-invasively.

KETOS: Clinical decision support and machine learning as a service - A training and deployment platform based on Docker, OMOP-CDM, and FHIR Web Services.

PloS one
BACKGROUND AND OBJECTIVE: To take full advantage of decision support, machine learning, and patient-level prediction models, it is important that models are not only created, but also deployed in a clinical setting. The KETOS platform demonstrated in...

Prevalence and Predictability of Low-Yield Inpatient Laboratory Diagnostic Tests.

JAMA network open
IMPORTANCE: Laboratory testing is an important target for high-value care initiatives, constituting the highest volume of medical procedures. Prior studies have found that up to half of all inpatient laboratory tests may be medically unnecessary, but...

Transfusion after total knee arthroplasty can be predicted using the machine learning algorithm.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: A blood transfusion after total knee arthroplasty (TKA) is associated with an increase in complication and infection rates. However, no studies have been conducted to predict transfusion after TKA using a machine learning algorithm. The purp...

Physiological interference reduction for near infrared spectroscopy brain activity measurement based on recursive least squares adaptive filtering and least squares support vector machines.

Computer assisted surgery (Abingdon, England)
Near infrared spectroscopy is the promising and noninvasive technique that can be used to detect the brain functional activation by monitoring the concentration alternations in the haemodynamic concentration. The acquired NIRS signals are commonly co...

Association of time to colonoscopy after a positive fecal test result and fecal hemoglobin concentration with risk of advanced colorectal neoplasia.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
BACKGROUND: We evaluated the risk of advanced colorectal neoplasia (ACRN) and colorectal cancer (CRC) according to time to colonoscopy after positive fecal immunochemical test (FIT), fecal hemoglobin concentration, and combination of both.