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AI in Public Health
Artificial Intelligence (AI) is revolutionizing public health by enhancing disease surveillance, predicting outbreaks, and optimizing resource allocation. By analyzing vast datasets, AI can identify patterns and provide insights for timely interventions, improving population health outcomes. It aids in personalized healthcare by tailoring prevention strategies and treatments to individual needs. AI-driven tools, like chatbots and health apps, improve accessibility to health information, empowering communities. Additionally, AI supports research by accelerating data analysis in epidemiology and public health studies. However, ethical considerations and data privacy remain crucial challenges to address in leveraging AI for public health.
About the Speaker
Dr. Umashankar
Professor and Managing Director Arogyati Private Limited, Banglore
Dr.Umashankar Subramanian is an Academician, Entrepreneur, Administrator and Mentor. He graduated BHMS from Government Homoeopathic Medical College and Hospital Bangalore, and Masters in Public Health from University of South Florida, Tampa, USA. He has 17 years of experience in homeopathic clinical practice and public health. He is Former Principal of Padmashree School of Public Health. He is Chairman, Scientific Committee, Government Homoeopathic Medical College, Karnataka and also Vice President: National Association of Palliative care and Integrated Medicine, Karnataka Chapter. He presented papers at national and international conferences, and also published papers in national and international journals.
Upcoming Case Discussions
Treatment of Renal Disease in ANCA Vasculitis
The treatment of renal disease in ANCA-associated vasculitis (AAV) typically involves a combination of immunosuppressive therapies to control inflammation and prevent further kidney damage. First-line treatment often includes high-dose corticosteroids and cyclophosphamide or rituximab, both of which help to induce remission by targeting the underlying immune system dysfunction. In cases of kidney failure or rapidly progressive glomerulonephritis, plasmapheresis may be used to remove circulating autoantibodies. Once remission is achieved, maintenance therapy with lower doses of immunosuppressants, such as azathioprine or mycophenolate mofetil, is used to prevent relapses and preserve kidney function.
NIV in Acute Respiratory Failure
Dr Viny Kantroo is a Chest, Critical Care & Sleep medicine specialist based in Delhi, boasting over more than 15 years of professional experience. She is currently practising as a full time Senior consultant in Indraprastha Apollo Hospitals New Delhi and Visiting Consultant Apollo Hospitals Noida in the department of Respiratory, Critical Care and Sleep Medicine. She is recognised for her expertise in various aspects of Chest medicine, which includes EBUS (Convex probe, Radial), Bronchoscopic procedures, pleural effusion management, interstitial lung disease, Covid-19, lung cancer, pneumonia, and intensive care patient management. Dr Kantroo is renowned not only for her medical proficiency but also for her empathy and positive attitude towards patient care. Patients consulting with Dr Viny can be assured of receiving an accurate diagnosis and effective treatment, thanks to her commitment to prompt and comprehensive care.
Pulmonary Tuberculosis: Challenges in Diagnosis
Diagnosing pulmonary tuberculosis (TB) poses significant challenges, particularly in resource-limited settings. The disease often mimics other respiratory conditions, leading to delayed or missed diagnoses. Traditional diagnostic methods like sputum smear microscopy have limited sensitivity, especially in HIV co-infected or low-bacterial-load patients. Advanced techniques such as GeneXpert and culture tests, though more accurate, are often unavailable in remote areas. Children and immunocompromised patients present additional hurdles due to atypical symptoms and difficulty obtaining diagnostic samples. Non-specific imaging findings further complicate diagnosis. Addressing these challenges requires expanded access to molecular diagnostics, improved point-of-care tools, and greater healthcare awareness.
AI in Genetics and Genomics
AI is revolutionizing genetics and genomics by enabling faster and more accurate analysis of complex genetic data. Machine learning algorithms can identify patterns in DNA sequences, helping to discover new genetic variants linked to diseases. Additionally, AI assists in predicting gene functions, personalizing medicine, and accelerating drug development. Its integration promises significant advancements in understanding genetic diseases and improving healthcare outcomes.
Management of Pediatric Type 1 Diabetes
Pediatric type 1 diabetes management focuses on maintaining glycemic control while supporting normal growth. Insulin therapy, via multiple daily injections or pumps, is essential, with doses adjusted based on blood glucose monitoring or continuous glucose monitoring (CGM). Nutrition plans emphasizing carbohydrate counting and balanced meals are crucial, alongside adjustments for physical activity to prevent glucose fluctuations. Education for families on recognizing hypo- and hyperglycemia symptoms and managing sick days is vital. Regular follow-ups with a pediatric endocrinologist help monitor HbA1c levels, growth, and complications. Psychosocial support is key for ensuring adherence and addressing emotional challenges.
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Dr. Umashankar's Talks on Assimilate
- 5th -Dec -2024, TIME : 5:00PM TO 6:00 PM
- 0
Artificial Intelligence (AI) is revolutionizing public health by enhancing disease surveillance, predicting outbreaks, and optimizing resource allocation. By analyzing vast datasets, AI can identify patterns and provide insights for timely interventions, improving population health outcomes. It aids in personalized healthcare by tailoring prevention strategies and treatments to individual needs. AI-driven tools, like chatbots and health apps, improve accessibility to health information, empowering communities. Additionally, AI supports research by accelerating data analysis in epidemiology and public health studies. However, ethical considerations and data privacy remain crucial challenges to address in leveraging AI for public health.
- 5th -Dec -2024, TIME : 5:00PM TO 6:00 PM
- 0
Artificial Intelligence (AI) is revolutionizing public health by enhancing disease surveillance, predicting outbreaks, and optimizing resource allocation. By analyzing vast datasets, AI can identify patterns and provide insights for timely interventions, improving population health outcomes. It aids in personalized healthcare by tailoring prevention strategies and treatments to individual needs. AI-driven tools, like chatbots and health apps, improve accessibility to health information, empowering communities. Additionally, AI supports research by accelerating data analysis in epidemiology and public health studies. However, ethical considerations and data privacy remain crucial challenges to address in leveraging AI for public health.