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The Role of AI in Ophthalmology
Artificial Intelligence (AI) is revolutionizing ophthalmology by enhancing diagnostic accuracy and improving patient care. AI-powered tools, such as deep learning algorithms, are capable of detecting eye diseases like diabetic retinopathy, glaucoma, and age-related macular degeneration with remarkable precision. These technologies enable early detection and intervention, often outperforming traditional methods. AI also streamlines workflows by analyzing imaging data rapidly, freeing up time for ophthalmologists to focus on patient care. Furthermore, AI-driven telemedicine solutions are expanding access to eye care in remote and underserved areas. As the field advances, AI holds the potential to transform ophthalmology into a more efficient and patient-centered discipline.
About the Speaker
Dr. Manish Chabra
Consultant Ophthalmologist, Apollo Hospitals, Chandigarh
Dr. Manish Chhabra is an Ophthalmologist with a clinical experience of 9 years including 1 year of experience in Glaucoma Subspecialty at PGIMER, Chandigarh. He is currently practicing in Apollo clinic & CHD city hospital, Sector 8C, Chandigarh. He has a special interest in teaching and has been associated with Delhi Academy of Medical Sciences (DAMS) from past 8 years where he has taught thousands of students both in India & abroad
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.
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.
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.
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. Manish Chabra 's Talks on Assimilate
- 10th -Dec -2024, TIME : 5:00PM TO 6:00 PM
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Artificial Intelligence (AI) is revolutionizing ophthalmology by enhancing diagnostic accuracy and improving patient care. AI-powered tools, such as deep learning algorithms, are capable of detecting eye diseases like diabetic retinopathy, glaucoma, and age-related macular degeneration with remarkable precision. These technologies enable early detection and intervention, often outperforming traditional methods. AI also streamlines workflows by analyzing imaging data rapidly, freeing up time for ophthalmologists to focus on patient care. Furthermore, AI-driven telemedicine solutions are expanding access to eye care in remote and underserved areas. As the field advances, AI holds the potential to transform ophthalmology into a more efficient and patient-centered discipline.