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Machine Learning - AI Medical Compendium

AIMC Topic: Machine Learning

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Investigation on explainable machine learning models to predict chronic kidney diseases.

Scientific reports Feb 14, 2024
Chronic kidney disease (CKD) is a major worldwide health problem, affecting a large proportion of the world's population and leading to higher morbidity and death rates. The early stages of CKD sometimes present without visible symptoms, causing pati...
Bayes Theorem Calcium Compounds Oxides Machine Learning Glycated Hemoglobin Humans Quality of Life Artificial Intelligence Renal Insufficiency, Chronic
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Enhancing heart failure treatment decisions: interpretable machine learning models for advanced therapy eligibility prediction using EHR data.

BMC medical informatics and decision making Feb 14, 2024
Timely and accurate referral of end-stage heart failure patients for advanced therapies, including heart transplants and mechanical circulatory support, plays an important role in improving patient outcomes and saving costs. However, the decision-mak...
Bayes Theorem Heart Failure Risk Factors Comorbidity Humans Machine Learning
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Artificial Intelligence in Operating Room Management.

Journal of medical systems Feb 14, 2024
This systematic review examines the recent use of artificial intelligence, particularly machine learning, in the management of operating rooms. A total of 22 selected studies from February 2019 to September 2023 are analyzed. The review emphasizes th...
Machine Learning Efficiency, Organizational Operating Rooms Humans
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A low-cost machine learning framework for predicting drug-drug interactions based on fusion of multiple features and a parameter self-tuning strategy.

Physical chemistry chemical physics : PCCP Feb 14, 2024
Poly-drug therapy is now recognized as a crucial treatment, and the analysis of drug-drug interactions (DDIs) offers substantial theoretical support and guidance for its implementation. Predicting potential DDIs using intelligent algorithms is an eme...
Machine Learning Algorithms Drug Interactions
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Enhancing machine learning-based sentiment analysis through feature extraction techniques.

PloS one Feb 14, 2024
A crucial part of sentiment classification is featuring extraction because it involves extracting valuable information from text data, which affects the model's performance. The goal of this paper is to help in selecting a suitable feature extraction...
Algorithms Humans Sentiment Analysis Machine Learning
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A comprehensive review of machine learning and its application to dairy products.

Critical reviews in food science and nutrition Feb 13, 2024
Machine learning (ML) technology is a powerful tool in food science and engineering offering numerous advantages, from recognizing patterns and predicting outcomes to customizing and adjusting to individual needs. Its further development can enable r...
Food Handling Dairying Dairy Products Animals Food Technology Humans Machine Learning Algorithms
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A machine-learning model based on dynamic contrast-enhanced MRI for preoperative differentiation between hepatocellular carcinoma and combined hepatocellular-cholangiocarcinoma.

Clinical radiology Feb 13, 2024
AIM: To establish a machine-learning model based on dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) to differentiate combined hepatocellular-cholangiocarcinoma (cHCC-CC) from hepatocellular carcinoma (HCC) before surgery.
Liver Neoplasms Carcinoma, Hepatocellular Contrast Media Male Middle Aged Cholangiocarcinoma Magnetic Resonance Imaging Diagnosis, Differential Bile Duct Neoplasms Machine Learning Humans Retrospective Studies Aged Female Adult Sensitivity and Specificity
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Potential of radiomics analysis and machine learning for predicting brain metastasis in newly diagnosed lung cancer patients.

Clinical radiology Feb 13, 2024
AIM: To explore the potential of utilising radiomics analysis and machine-learning models that incorporate intratumoural and peritumoural regions of interest (ROIs) for predicting brain metastasis (BM) in newly diagnosed lung cancer patients.
Adult Radiomics Brain Neoplasms Male Middle Aged Lung Neoplasms Tomography, X-Ray Computed Female Humans Aged Brain Machine Learning Retrospective Studies Predictive Value of Tests
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Malnutrition risk assessment using a machine learning-based screening tool: A multicentre retrospective cohort.

Journal of human nutrition and dietetics : the official journal of the British Dietetic Association Feb 13, 2024
BACKGROUND: Malnutrition is associated with increased morbidity, mortality, and healthcare costs. Early detection is important for timely intervention. This paper assesses the ability of a machine learning screening tool (MUST-Plus) implemented in re...
Female Hospitalization Aged Humans Machine Learning Retrospective Studies Risk Assessment Mass Screening Malnutrition New York City Male Middle Aged Nutrition Assessment Aged, 80 and over Adult
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Meta-lasso: new insight on infection prediction after minimally invasive surgery.

Medical & biological engineering & computing Feb 13, 2024
Surgical site infection (SSI) after minimally invasive lung cancer surgery constitutes an important factor influencing the direct and indirect economic implications, patient prognosis, and the 5-year survival rate for early-stage lung cancer patients...
Aged Male Middle Aged Algorithms Retrospective Studies Female Humans Machine Learning Lung Neoplasms Minimally Invasive Surgical Procedures Surgical Wound Infection
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