AIMC Topic: Steroids

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Tualang honey versus steroid impregnated nasal dressing following endoscopic sinus surgery: a randomized controlled trial.

Journal of complementary & integrative medicine Dec 21, 2020
OBJECTIVES: Recurrence rate of nasal polyps is high following endoscopic sinus surgery. To improve the surgical outcome, steroid impregnated nasal dressing is used postoperatively We aimed to compare the effect of Tualang honey impregnated nasal dres...
Double-Blind Method Humans Bandages Prospective Studies Honey Treatment Outcome Steroids Paranasal Sinuses Rhinitis Chronic Disease
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Use of Steroid Profiling Combined With Machine Learning for Identification and Subtype Classification in Primary Aldosteronism.

JAMA network open Sep 1, 2020
IMPORTANCE: Most patients with primary aldosteronism, a major cause of secondary hypertension, are not identified or appropriately treated because of difficulties in diagnosis and subtype classification. Applications of artificial intelligence combin...
Humans Poland Hyperaldosteronism Male Machine Learning Middle Aged Female Steroids Adult
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Developing an Improved Statistical Approach for Survival Estimation in Bone Metastases Management: The Bone Metastases Ensemble Trees for Survival (BMETS) Model.

International journal of radiation oncology, biology, physics May 22, 2020
PURPOSE: To determine whether a machine learning approach optimizes survival estimation for patients with symptomatic bone metastases (SBM), we developed the Bone Metastases Ensemble Trees for Survival (BMETS) to predict survival using 27 prognostic ...
Area Under Curve Analgesics, Opioid Palliative Care Time Factors Pelvic Bones Bone Neoplasms Kaplan-Meier Estimate Life Expectancy Karnofsky Performance Status Blood Cell Count Spinal Neoplasms Proportional Hazards Models Algorithms Prognosis Female Middle Aged Steroids Reproducibility of Results Male Humans Machine Learning
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Steroid identification via deep learning retention time predictions and two-dimensional gas chromatography-high resolution mass spectrometry.

Journal of chromatography. A Oct 28, 2019
Untargeted steroid identification represents a great analytical challenge even when using sophisticated technology such as two-dimensional gas chromatography coupled to high resolution mass spectrometry (GC × GCHRMS) due to the chemical similarity of...
Static Electricity Support Vector Machine Steroids Least-Squares Analysis Deep Learning Gas Chromatography-Mass Spectrometry Neural Networks, Computer
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The Use of Transdermal Estrogen in Castrate-resistant, Steroid-refractory Prostate Cancer.

Clinical genitourinary cancer Oct 10, 2019
BACKGROUND: Androgen-deprivation therapy is the mainstay of treatment for metastatic prostate cancer. Corticosteroids and estrogens are also useful agents in castration-resistant prostate cancer (CRPC). However, oral estrogens are associated with thr...
Middle Aged Steroids Quality of Life Aged Aged, 80 and over Humans Male Prostatic Neoplasms, Castration-Resistant Prognosis Estrogens Administration, Cutaneous Follow-Up Studies Drug Resistance, Neoplasm
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Using Machine Learning to Aid the Interpretation of Urine Steroid Profiles.

Clinical chemistry Aug 10, 2018
BACKGROUND: Urine steroid profiles are used in clinical practice for the diagnosis and monitoring of disorders of steroidogenesis and adrenal pathologies. Machine learning (ML) algorithms are powerful computational tools used extensively for the reco...
Predictive Value of Tests Datasets as Topic Clinical Chemistry Tests Algorithms Adrenal Gland Diseases Steroids Decision Support Systems, Clinical Humans Machine Learning
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Revealing disease-associated pathways by network integration of untargeted metabolomics.

Nature methods Aug 1, 2016
Uncovering the molecular context of dysregulated metabolites is crucial to understand pathogenic pathways. However, their system-level analysis has been limited owing to challenges in global metabolite identification. Most metabolite features detecte...
Algorithms Steroids Metabolomics Fatty Acids Sphingolipids Databases, Protein Metabolic Networks and Pathways Humans Neural Networks, Computer Machine Learning Huntington Disease
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Potential of atmospheric pressure chemical ionization source in gas chromatography tandem mass spectrometry for the screening of urinary exogenous androgenic anabolic steroids.

Analytica chimica acta Dec 17, 2015
The atmospheric pressure chemical ionization (APCI) source for gas chromatography-mass spectrometry analysis has been evaluated for the screening of 16 exogenous androgenic anabolic steroids (AAS) in urine. The sample treatment is based on the strate...
Humans Steroids Gas Chromatography-Mass Spectrometry Atmospheric Pressure Anabolic Agents
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Machine Learning and Large Language Models for Modeling Complex Toxicity Pathways and Predicting Steroidogenesis.

Environmental science & technology Jul 15, 2025
High-throughput screening and computational models have been effective in predicting chemical interactions with estrogen and androgen receptors, but similar approaches for steroidogenesis remain limited. To address this gap, we developed general ster...
Machine Learning Steroids Cell Line, Tumor Large Language Models Humans
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Predicting treatment outcome in congenital adrenal hyperplasia using urine steroidomics and machine learning.

European journal of endocrinology Jun 30, 2025
OBJECTIVE: Treatment monitoring of individuals with congenital adrenal hyperplasia (CAH) remains unsatisfactory. Comprehensive 24 h urine steroid profiling provides detailed insight into adrenal steroid pathways. We investigated whether 24 h urine st...
Child, Preschool Child Treatment Outcome Steroids Adolescent Cohort Studies Humans Female Gas Chromatography-Mass Spectrometry Male Adrenal Hyperplasia, Congenital Machine Learning Prospective Studies
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