A5060069131- Oral and Maxillofacial Pathology
- Oral and gingival health research
- Periodontal Regeneration and Treatments
- Endodontics and Root Canal Treatments
- Cardiac Health and Mental Health
- Salivary Gland Disorders and Functions
- Dental Implant Techniques and Outcomes
- Growth Hormone and Insulin-like Growth Factors
- Artificial Intelligence in Healthcare and Education
- Cardiovascular Function and Risk Factors
- Long-Term Effects of COVID-19
- Drug-Induced Hepatotoxicity and Protection
- Soft tissue tumor case studies
- COVID-19 Clinical Research Studies
- Bone Tissue Engineering Materials
- dental development and anomalies
- Eicosanoids and Hypertension Pharmacology
- Machine Learning in Healthcare
- Vitamin K Research Studies
- Drug-Induced Adverse Reactions
- Medical and Biological Ozone Research
- Diabetes Treatment and Management
- Synthesis and biological activity
- Veterinary Orthopedics and Neurology
- Cancer, Stress, Anesthesia, and Immune Response
Narayana Dental College and Hospital
2023-2024
Universidade de São Paulo
1971-1992
BACKGROUND Prediabetes is a well-established risk factor for major adverse cardiac and cerebrovascular events (MACCE). However, the relationship between prediabetes MACCE in atrial fibrillation (AF) patients has not been extensively studied. Therefore, this study aimed to establish link AF patients. AIM To investigate METHODS We used National Inpatient Sample (2019) relevant ICD-10 CM codes identify hospitalizations with categorized them into groups without prediabetes, excluding diabetics....
Body Mass Index (BMI) has a significant impact on Coronavirus disease (COVID-19) patient outcomes; however, major adverse cardiac and cerebrovascular outcomes in patients with severe sepsis have been poorly understood. Our study aims to explore provide insight into its association. This is an observational looking at the of BMI COVID-19-severe hospitalizations. The primary are adjusted odds all-cause in-hospital mortality, respiratory failure, events (MACCE), which include acute myocardial...
Cardiovascular diseases (CVDs) remain the leading cause of mortality. Traditional approaches to diagnosing and treating CVDs often involve interpretation, which can lead errors. The emergence Artificial Intelligence (AI) Machine Learning aids management CVDs. AI examines amounts data identifies patterns offering solutions for disease detection, risk prediction, patient care. American Heart Association's 2023 Scientific Sessions (AHA23) showcased studies that highlight AIs potential...
Cardiovascular diseases (CVDs) remain the leading cause of mortality. Traditional approaches to diagnosing and treating CVDs often involve interpretation, which can lead errors. The emergence Artificial Intelligence (AI) Machine Learning aids management CVDs. AI examines amounts data identifies patterns offering solutions for disease detection, risk prediction, patient care. American Heart Association's 2023 Scientific Sessions (AHA23) showcased studies that highlight AIs potential...