Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
Real-World Efficacy and Safety of Avelumab Plus Axitinib in Metastatic Renal Cell Carcinoma: Results from the Ambispective RAVE-Renal Study.
Curr Oncol
December 2024
Saint-Petersburg State University, 199034 Saint-Petersburg, Russia.
Background: The RAVE-Renal study was conducted to evaluate the real-world efficacy and safety of avelumab plus axitinib as a first-line therapy for patients with metastatic renal cell carcinoma (mRCC).
Methods: RAVE-Renal was a multicenter, noninterventional, ambispective study with both retrospective and prospective components. The study included adult patients with histologically confirmed mRCC, measurable disease per RECIST version 1.
Factors associated with the delay in diagnosis of extrapulmonary tuberculosis at the patient and health system level: A study from a rural setting in India.
PLoS One
January 2025
Centre for International Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
Background: With the proportion of tuberculosis cases that are extrapulmonary tuberculosis (EPTB) increasing in recent years, understanding and addressing factors contributing to the prolonged time to diagnosis (TTD) of EPTB patients is vital.
Methods: We enrolled presumptive EPTB patients for a cohort study from 2018-2020 in Ujjain, India. Based on a structured questionnaire, the patients were interviewed for socio-demographic and clinical information, including previously visited health facilities (HF) for this illness.
The biomedical applications of artificial intelligence: an overview of decades of research.
J Drug Target
January 2025
Department of Pharmaceutics, Bharat Pharmaceutical Technology, Amtali, Agartala, Tripura, India.
A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attracted significant interest in biomedical research due to its features: (i) better patient care through early diagnosis and detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) lowering medical costs; (vi) reducing morbidity and mortality; (vii) enhancing performance; (viii) enhancing precision; and (ix) time efficiency. Quantitative metrics are crucial for evaluating AI implementations, providing insights, enabling informed decisions, and measuring the impact of AI-driven initiatives, thereby enhancing transparency, accountability, and overall impact.
View Article and Find Full Text PDFMedical Marijuana Documentation Practices in Patient Electronic Health Records: Retrospective Observational Study Using Smart Data Elements and a Review of Medical Records.
JMIR Form Res
December 2024
Autism and Developmental Medicine Institute, Geisinger, Lewisburg, PA, United States.
Background: Medical marijuana (MMJ) is available in Pennsylvania, and participation in the state-regulated program requires patient registration and receiving certification by an approved physician. Currently, no integration of MMJ certification data with health records exists in Pennsylvania that would allow clinicians to rapidly identify patients using MMJ, as exists with other scheduled drugs. This absence of a formal data sharing structure necessitates tools aiding in consistent documentation practices to enable comprehensive patient care.
View Article and Find Full Text PDFAssociation of State Cannabis Legalization With Cannabis Use Disorder and Cannabis Poisoning.
JAMA Psychiatry
December 2024
Institute for Biomedical Informatics, College of Medicine, University of Kentucky, Lexington.
Importance: Whether state implementation of medical and recreational cannabis laws is associated with increased cannabis use disorder (CUD) and/or cannabis poisoning among adults is not evident.
Objective: To examine state-level medical and recreational cannabis laws' associations with CUD and cannabis poisoning, overall and by sex and age subgroups.
Design, Setting, And Participants: In this longitudinal cohort study, state-level CUD and cannabis poisoning diagnoses from January 2011 to December 2021 were examined across all 50 US states and the District of Columbia before and after the implementation of medical and recreational cannabis laws (MCLs and RCLs, respectively) using a staggered adoption difference-in-differences approach.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!