AIMC Topic: Bilirubin
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Establishment of predictive models for postoperative delirium in elderly patients after knee/hip surgery based on total bilirubin concentration: machine learning algorithms.
BMC anesthesiology
Jul 30, 2025
BACKGROUND: With the aging demographic on the rise, we're seeing a spike in the occurrence of postoperative delirium (POD). Our research aims to delve into the connection between plasma bilirubin levels and postoperative delirium, with the goal of cr...
MAMSI: Integration of Multiassay Liquid Chromatography-Mass Spectrometry Metabolomics Data Using Multiview Machine Learning.
Analytical chemistry
Jul 10, 2025
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...
A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein.
Scientific reports
Jul 1, 2025
Metabolic Syndrome (MetS) comprises a clustering of conditions that significantly increase the risk of heart disease, stroke, and diabetes. Timely detection and intervention are crucial in preventing severe health outcomes. In this study, we implemen...
Artificial intelligence-based non-invasive bilirubin prediction for neonatal jaundice using 1D convolutional neural network.
Scientific reports
Apr 4, 2025
Neonatal jaundice, characterized by elevated bilirubin levels causing yellow discoloration of the skin and eyes in newborns, is a critical condition requiring accurate and timely diagnosis. This study proposes a novel approach using 1D Convolutional ...
Machine Learning Models predicting Decompensation in Cirrhosis.
Journal of gastrointestinal and liver diseases : JGLD
Mar 27, 2025
BACKGROUND AND AIMS: Decompensation of cirrhosis significantly decreases survival, thus, prevention of complications is paramount. We used machine learning techniques to identify parameters predicting decompensation.
Feasibility study of texture-based machine learning approach for early detection of neonatal jaundice.
Scientific reports
Feb 22, 2025
Untreated neonatal jaundice can have severe consequences. Effective screening for neonatal jaundice can prevent long-term complications in infants. Non-invasive approaches may be beneficial in settings with limited resources. This feasibility study e...
Artificial Intelligence non-invasive methods for neonatal jaundice detection: A review.
Artificial intelligence in medicine
Feb 19, 2025
Neonatal jaundice is a common and potentially fatal health condition in neonates, especially in low and middle income countries, where it contributes considerably to neonatal morbidity and death. Traditional diagnostic approaches, such as Total Serum...
Prediction of insulin resistance using multiple adaptive regression spline in Chinese women.
Endocrine journal
Feb 1, 2025
Insulin resistance (IR) is the core for type 2 diabetes and metabolic syndrome. The homeostasis assessment model is a straightforward and practical tool for quantifying insulin resistance (HOMA-IR). Multiple adaptive regression spline (MARS) is a mac...
Preoperative blood and CT-image nutritional indicators in short-term outcomes and machine learning survival framework of intrahepatic cholangiocarcinoma.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Jan 30, 2025
BACKGROUND&AIMS: Intrahepatic cholangiocarcinoma (iCCA) is aggressive with limited treatment and poor prognosis. Preoperative nutritional status assessment is crucial for predicting outcomes in patients. This study aimed to compare the predictive cap...
Bilirubin
Hepatectomy
Bile Duct Neoplasms
Nutritional Status
Preoperative Period
Middle Aged
Nutrition Assessment
Postoperative Complications
Neoplasm Recurrence, Local
Intra-Abdominal Fat
Serum Albumin
Cholangiocarcinoma
Subcutaneous Fat
Humans
Machine Learning
Prognosis
Retrospective Studies
Tomography, X-Ray Computed
Female
Aged
Survival Rate
Male
Machine learning model to predict the adherence of tuberculosis patients experiencing increased levels of liver enzymes in Indonesia.
PloS one
Jan 24, 2025
Indonesia is still the second-highest tuberculosis burden country in the world. The antituberculosis adverse drug reaction and adherence may influence the success of treatment. The objective of this study is to define the model for predicting the adh...
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