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   Articles with "predicting adverse" as a keyword



Machine learning methods for predicting adverse drug events: A systematic review.

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recommendations! Published in 2025 at "British journal of clinical pharmacology"

DOI: 10.1002/bcp.70377

Abstract: Predicting adverse drug events (ADEs) in outpatient settings is crucial for improving medication safety, identifying high-risk patients and reducing health-care costs. While traditional methods struggle with the complexity of health-care data, machine learning (ML) models… read more here.

Keywords: adverse drug; systematic review; machine learning; predicting adverse ... See more keywords

Performance of Ductus Venosus Doppler (at 11–13 + 6 Weeks) in Predicting Adverse Fetal Outcomes in Indian Population

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recommendations! Published in 2022 at "Journal of Ultrasound in Medicine"

DOI: 10.1002/jum.15976

Abstract: The objective of this study is to examine the performance of Ductus venosus (DV) Doppler done at the routine first trimester screening (11–13 + 6 weeks) in predicting the adverse fetal outcomes in Indian population. read more here.

Keywords: weeks predicting; ductus venosus; performance ductus; venosus doppler ... See more keywords

Risk Stratification Index 3.0, a Broad Set of Models for Predicting Adverse Events during and after Hospital Admission

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recommendations! Published in 2022 at "Anesthesiology"

DOI: 10.1097/aln.0000000000004380

Abstract: Background: Risk stratification helps guide appropriate clinical care. Our goal was to develop and validate a broad suite of predictive tools based on International Classification of Diseases, Tenth Revision, diagnostic and procedural codes for predicting… read more here.

Keywords: risk stratification; hospital admission; risk; predicting adverse ... See more keywords

External validation of a risk‐scoring model for predicting adverse perinatal outcomes in pregnancies with fetal growth restriction

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recommendations! Published in 2025 at "Journal of Obstetrics and Gynaecology Research"

DOI: 10.1111/jog.16319

Abstract: This study aimed to validate the Prince of Songkla University (PSU) risk‐scoring model for predicting adverse perinatal outcomes in pregnancies with an antenatal diagnosis of fetal growth restriction (FGR) in an independent cohort. read more here.

Keywords: scoring model; perinatal outcomes; adverse perinatal; model predicting ... See more keywords

An External Validation Study of the Oakland and Glasgow-Blatchford Scores for Predicting Adverse Outcomes of Acute Lower Gastrointestinal Bleeding in an Asian Population

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recommendations! Published in 2021 at "Gastroenterology Research and Practice"

DOI: 10.1155/2021/8674367

Abstract: Aims This study is aimed at (1) validating the performance of Oakland and Glasgow-Blatchford (GBS) scores and (2) comparing these scores with the SALGIB score in predicting adverse outcomes of acute lower gastrointestinal bleeding (ALGIB)… read more here.

Keywords: predicting adverse; adverse outcomes; study; bleeding ... See more keywords
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What is the accuracy of multi-parametric magnetic resonance imaging in predicting adverse pathology in patients undergoing radical prostatectomy?

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recommendations! Published in 2018 at "Journal of Clinical Oncology"

DOI: 10.1200/jco.2018.36.6_suppl.139

Abstract: 139Background: Few studies have examined the accuracy of preoperative multi-parametric magnetic resonance imaging (MP-MRI) in predicting adverse pathological features in patients undergoing radical prostatectomy (RP) for localized prostate cancer (PCa). Methods: We retrospectively analyzed the… read more here.

Keywords: predicting adverse; resonance imaging; parametric magnetic; magnetic resonance ... See more keywords

Performance of Machine Learning Algorithms for Predicting Adverse Outcomes in Community-Acquired Pneumonia

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recommendations! Published in 2022 at "Frontiers in Bioengineering and Biotechnology"

DOI: 10.3389/fbioe.2022.903426

Abstract: Background: The ability to assess adverse outcomes in patients with community-acquired pneumonia (CAP) could improve clinical decision-making to enhance clinical practice, but the studies remain insufficient, and similarly, few machine learning (ML) models have been… read more here.

Keywords: adverse outcomes; machine learning; acquired pneumonia; community acquired ... See more keywords

Machine Learning Models for Predicting Adverse Pregnancy Outcomes in Pregnant Women with Systemic Lupus Erythematosus

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recommendations! Published in 2023 at "Diagnostics"

DOI: 10.3390/diagnostics13040612

Abstract: Predicting adverse outcomes is essential for pregnant women with systemic lupus erythematosus (SLE) to minimize risks. Applying statistical analysis may be limited for the small sample size of childbearing patients, while the informative medical records… read more here.

Keywords: lupus erythematosus; machine learning; pregnant women; systemic lupus ... See more keywords