Various sub-fields within the medical domain where AI can be of assistance

CNN based Projects/Papers

  1. DNA Sequence Classification: a. DNA sequence classification for identifying genetic variations b. Gene function prediction from DNA sequences c. Classification of DNA sequences for disease risk assessment
  2. Lung Cancer: a. Lung nodule detection b. Lung nodule classification c. Lung cancer staging
  3. Breast Cancer: a. Mammogram analysis for breast cancer detection b. Breast cancer subtype classification c. Breast tumor segmentation
  4. Brain Tumor: a. Brain tumor detection b. Brain tumor segmentation c. Brain tumor subtype classification
  5. Diabetic Retinopathy: a. Retinal image analysis for diabetic retinopathy detection b. Diabetic macular edema detection c. Retinal vessel segmentation
  6. Skin Cancer: a. Melanoma detection and classification b. Non-melanoma skin cancer detection c. Skin lesion segmentation
  7. Cardiac Disease: a. Cardiac image analysis for heart disease diagnosis b. Left ventricle segmentation c. Coronary artery disease detection
  8. Bone Fracture: a. X-ray analysis for bone fracture detection b. Fracture localization and classification c. Orthopedic implant placement analysis
  9. Colon Polyp: a. Colonoscopy analysis for polyp detection b. Polyp segmentation and classification c. Adenoma detection in colonoscopy images
  10. Gastrointestinal Disease: a. Gastric lesion detection and classification b. Colorectal cancer detection c. Esophageal disease diagnosis
  11. Liver Disease: a. Hepatic lesion detection b. Liver fibrosis staging c. Liver tumor segmentation
  12. Prostate Cancer: a. Prostate tumor detection and segmentation b. Gleason score prediction c. Prostate cancer recurrence prediction
  13. Ophthalmic Diseases: a. Glaucoma detection and classification b. Age-related macular degeneration diagnosis c. Retinopathy of prematurity detection
  14. Pneumonia: a. Chest X-ray analysis for pneumonia detection b. Viral vs. bacterial pneumonia differentiation c. Pneumonia severity assessment
  15. Tuberculosis: a. Tuberculosis detection from chest imaging b. Tuberculosis lesion segmentation c. Tuberculosis drug resistance prediction
  16. COVID-19: a. Chest CT scan analysis for COVID-19 detection b. COVID-19 severity prediction c. COVID-19 image-based prognosis
  17. Alzheimer’s Disease: a. Brain MRI analysis for Alzheimer’s disease detection b. Hippocampus segmentation for Alzheimer’s disease progression assessment c. Alzheimer’s disease subtype classification
  18. Stroke: a. Brain MRI analysis for stroke detection b. Ischemic vs. hemorrhagic stroke differentiation c. Stroke lesion segmentation
  19. Arthritis: a. Rheumatoid arthritis detection and classification b. Osteoarthritis diagnosis c. Hand joint segmentation for arthritis assessment
  20. Scoliosis: a. Scoliosis detection and severity assessment b. Spine curvature measurement c. Scoliosis brace fitting analysis
  21. Kidney Disease: a. Kidney stone detection and classification b. Renal cyst segmentation c. Chronic kidney disease progression prediction
  22. Dental Caries: a. Dental X-ray analysis for caries detection b. Caries severity assessment c. Tooth segmentation and alignment analysis
  23. Cervical Cancer: a. Cervical cytology analysis for cancer detection b. Cervical lesion segmentation c. HPV-related cervical cancer risk prediction
  24. Esophageal Cancer: a. Esophageal endoscopy analysis for cancer detection b. Barrett’s esophagus diagnosis c. Esophageal tumor staging
  25. Ovarian Cancer: a. Ovarian tumor detection and classification b. Ovarian cyst analysis c. Ovarian cancer prognosis prediction
  26. Pancreatic Cancer: a. Pancreatic tumor detection and segmentation b. Pancreatic cyst analysis c. Pancreatic cancer survival prediction
  27. Thyroid Disease: a. Thyroid nodule detection and classification b. Thyroid ultrasound analysis c. Thyroid cancer risk stratification
  28. Melanoma: a. Dermoscopy analysis for melanoma detection b. Melanoma segmentation and classification c. Skin cancer metastasis prediction
  29. Ultrasound Imaging: a. Fetal ultrasound analysis b. Cardiac ultrasound analysis c. Abdominal organ segmentation
  30. Mammogram Analysis: a. Breast density assessment b. Microcalcification detection c. Breast cancer recurrence prediction
  31. Endoscopy Analysis: a. Polyp detection and classification in gastrointestinal endoscopy b. Gastric ulcer detection c. Early gastric cancer detection
  32. Echocardiogram Analysis: a. Left ventricular function assessment b. Cardiac abnormality detection c. Congenital heart disease diagnosis
  33. Histopathology Analysis: a. Lymphoma classification b. Renal biopsy analysis c. Breast histopathology image analysis
  34. Nuclear Medicine Image Analysis: a. Thyroid scintigraphy analysis b. Bone scan analysis for metastases detection c. Myocardial perfusion analysis
  35. Radiology Report Generation: a. Automated report generation from medical images b. Abnormality description and localization c. Report summarization and structured information extraction
  36. Bone Age Assessment: a. Bone age estimation from X-rays b. Growth prediction and evaluation c. Puberty stage assessment
  37. Embryo Quality Evaluation in IVF: a. Embryo selection for in vitro fertilization b. Morphological assessment of embryos c. Blastocyst grading and selection
  38. Fetal Ultrasound Analysis: a. Fetal biometry measurement b. Fetal anomaly detection c. Placental localization and analysis
  39. Respiratory Disease Detection: a. Chronic obstructive pulmonary disease (COPD) diagnosis b. Asthma detection and severity assessment c. Interstitial lung disease classification
  40. Retinal Vessel Segmentation: a. Automated segmentation of retinal blood vessels b. Retinal vessel tortuosity analysis c. Vessel caliber measurement
  41. Image-Guided Surgery and Interventions: a. Surgical instrument tracking b. Real-time tumor margin delineation during surgery c. Catheter and guidewire positioning guidance
  42. Bladder Cancer: a. Bladder tumor detection and segmentation b. Bladder cancer grading c. Recurrence prediction in bladder cancer
  43. Leukemia: a. Blood cell classification for leukemia diagnosis b. Blast cell detection and counting c. Leukemia subtype classification
  44. Liver Fibrosis: a. Liver fibrosis staging from histopathology images b. Fibrosis regression monitoring c. Non-invasive fibrosis assessment using imaging
  45. Osteoporosis: a. Bone mineral density analysis for osteoporosis diagnosis b. Fracture risk prediction c. Vertebral compression fracture detection
  46. Gastric Cancer: a. Gastric tumor detection and segmentation b. Gastric cancer staging c. Survival prediction in gastric cancer
  47. Inflammatory Bowel Disease (IBD): a. Crohn’s disease detection and classification b. Ulcerative colitis assessment c. Inflammation localization in IBD
  48. Multiple Sclerosis: a. Multiple sclerosis lesion detection and segmentation b. Disease activity monitoring c. Progression prediction in multiple sclerosis
  49. Retinopathy of Prematurity (ROP): a. Retinal vessel analysis for ROP detection and grading b. Plus disease assessment c. ROP treatment decision support
  50. Pancreatitis: a. Acute pancreatitis detection b. Pancreatic pseudocyst identification c. Pancreatic necrosis segmentation
  51. Celiac Disease: a. Celiac disease diagnosis from small bowel biopsy images b. Villi atrophy assessment c. Gluten-free diet compliance monitoring
  52. Atrial Fibrillation: a. ECG analysis for atrial fibrillation detection b. Arrhythmia classification and diagnosis c. Stroke risk prediction in atrial fibrillation patients
  53. Glomerulonephritis: a. Glomerulus segmentation and classification b. Kidney biopsy analysis for glomerulonephritis diagnosis c. Disease activity assessment in glomerulonephritis
  54. Myocardial Infarction: a. Electrocardiogram (ECG) analysis for myocardial infarction detection b. Ischemic zone segmentation c. Infarct size quantification
  55. Retinal Detachment: a. Retinal image analysis for retinal detachment detection b. Identification of retinal breaks c. Assessment of retinal reattachment success
  56. Glioma: a. Glioma tumor detection and segmentation b. Glioma grading and subtyping c. Prediction of glioma patient survival
  57. Hematoma: a. Hematoma detection and segmentation from brain scans b. Hematoma volume quantification c. Localization of intracranial bleeding
  58. Gastric Ulcer: a. Endoscopy image analysis for gastric ulcer detection b. Ulcer size estimation c. Ulcer healing monitoring
  59. Atrial Fibrillation: a. ECG analysis for atrial fibrillation detection b. Arrhythmia classification c. Atrial fibrillation risk prediction
  60. Hematoma Detection: a. Detection of intracranial hematoma from head CT scans b. Hematoma segmentation and quantification c. Hemorrhage localization in trauma cases
  61. Myocardial Infarction: a. ECG analysis for myocardial infarction detection b. ST-segment elevation identification c. Infarct localization from cardiac imaging
  62. Cystic Fibrosis: a. Lung disease assessment in cystic fibrosis b. Bronchiectasis detection and monitoring c. Mucus plugging identification
  63. Deep Vein Thrombosis (DVT): a. DVT detection and localization from ultrasound images b. Thrombus segmentation and characterization c. DVT risk prediction in high-risk patients
  64. Hepatitis: a. Hepatitis detection and classification b. Hepatic fibrosis staging c. Viral hepatitis genotype identification
  65. Endometriosis: a. Endometriosis lesion detection and segmentation b. Endometrioma characterization c. Deep infiltrating endometriosis identification
  66. Retinal Detachment: a. Retinal detachment detection from fundus images b. Macula involvement assessment c. Surgical planning for retinal detachment repair
  67. Glomerulonephritis: a. Glomerulonephritis diagnosis from renal biopsy images b. Glomerular segmentation and quantification c. Disease activity monitoring
  68. Pulmonary Embolism: a. Pulmonary embolism detection from chest CT scans b. Embolus segmentation and localization c. Risk stratification in pulmonary embolism cases
  69. Glioma: a. Glioma tumor segmentation from brain MRI scans b. Glioma subtype classification c. Prediction of treatment response in glioma patients
  70. Amyotrophic Lateral Sclerosis (ALS): a. ALS disease progression monitoring from muscle imaging b. Muscle atrophy detection and quantification c. Survival prediction in ALS patients
  71. Aortic Aneurysm: a. Aortic aneurysm detection from medical imaging b. Aneurysm size and growth rate measurement c. Risk assessment for aortic rupture or dissection
  72. Influenza: a. Detection and classification of influenza strains b. Severity prediction in influenza cases c. Analysis of transmission patterns and outbreaks
  73. Psoriasis: a. Psoriasis lesion segmentation and quantification b. Psoriatic arthritis detection and classification c. Assessment of treatment response in psoriasis patients
  74. Retinitis Pigmentosa: a. Retinal structure analysis for retinitis pigmentosa diagnosis b. Disease progression monitoring c. Genetic mutation classification in retinitis pigmentosa
  75. Uterine Fibroids: a. Uterine fibroid detection and segmentation from ultrasound images b. Quantification of fibroid characteristics c. Prediction of fibroid-related symptoms and treatment response
  76. Polycystic Kidney Disease (PKD): a. Renal cyst detection and segmentation in PKD b. Kidney volume measurement for disease progression c. Risk prediction of renal complications in PKD patients

Eye Related

  1. Cataracts: AI can assist in diagnosing and grading cataracts by analyzing images of the eye lens.
  2. Glaucoma: AI algorithms can aid in early detection and monitoring of glaucoma by analyzing optic nerve and visual field data.
  3. Diabetic retinopathy: AI can detect signs of diabetic retinopathy by analyzing retinal images, enabling early intervention.
  4. Macular degeneration: AI algorithms can help identify and track the progression of age-related macular degeneration (AMD) through retinal imaging.
  5. Retinoblastoma: AI can assist in the early detection of retinoblastoma, a rare form of eye cancer, by analyzing retinal images.
  6. Dry eye syndrome: AI can help diagnose and monitor dry eye syndrome by analyzing tear film dynamics and ocular surface characteristics.
  7. Amblyopia (lazy eye): AI-based vision screening tools can aid in detecting amblyopia in children by analyzing visual acuity and stereoscopic vision.
  8. Strabismus: AI algorithms can help assess eye alignment and detect strabismus, a condition where the eyes are misaligned.
  9. Refractive errors: AI can assist in the precise measurement of refractive errors like myopia, hyperopia, and astigmatism, improving accuracy in prescribing corrective lenses.
  10. Retinal detachment: AI can aid in the early detection of retinal detachment by analyzing retinal imaging and identifying subtle changes.
  11. Optic neuritis: AI algorithms can assist in the diagnosis of optic neuritis, an inflammation of the optic nerve, by analyzing visual field data and optic disc appearance.
  12. Color blindness: AI-based color vision tests can help assess color vision deficiencies and distinguish between different types of color blindness.
  13. Retinitis pigmentosa: AI can assist in diagnosing and monitoring retinitis pigmentosa, a progressive degenerative eye disease, through retinal imaging analysis.
  14. Keratoconus: AI algorithms can aid in diagnosing and monitoring keratoconus, a corneal disorder, by analyzing corneal topography and biomechanical properties.
  15. Uveitis: AI can help detect and monitor uveitis, an inflammation of the uvea, by analyzing ocular imaging and identifying characteristic patterns.
  16. Corneal dystrophy: AI algorithms can assist in identifying and categorizing different types of corneal dystrophy based on clinical images and patient data.
  17. Retinal vascular diseases: AI can help detect and classify retinal vascular diseases such as retinal vein occlusion, diabetic macular edema, and hypertensive retinopathy using retinal imaging analysis.
  18. Optic disc edema: AI algorithms can aid in detecting optic disc edema, which can be a sign of various conditions such as papilledema or optic neuritis.
  19. Ocular tumors: AI can assist in the detection and classification of ocular tumors by analyzing imaging data and identifying abnormal tissue patterns.
  20. Ocular trauma: AI algorithms can help assess the severity and identify specific injuries in cases of ocular trauma through image analysis.
  21. Corneal ulcers: AI can aid in diagnosing and monitoring corneal ulcers by analyzing corneal imaging and identifying characteristic features.
  22. Ptosis (drooping eyelid): AI can help assess and quantify the degree of ptosis, assisting in the evaluation and monitoring of this condition.
  23. Optic nerve hypoplasia: AI algorithms can aid in diagnosing optic nerve hypoplasia by analyzing imaging data and identifying characteristic features.
  24. Ocular surface disorders: AI can assist in diagnosing and managing various ocular surface disorders like keratitis and conjunctivitis by analyzing clinical images and symptoms

Board Area :

  1. Medical imaging analysis
  2. Radiology and diagnostic support
  3. Pathology and histopathology analysis
  4. Automated tumor detection and classification
  5. Computer-aided diagnosis (CAD)
  6. Predictive analytics for disease outcomes
  7. Drug discovery and development
  8. Genomics and personalized medicine
  9. Clinical decision support systems
  10. Electronic health record (EHR) management
  11. Natural language processing for medical documentation
  12. Medical data mining and knowledge discovery
  13. Disease risk assessment and prevention
  14. Clinical trial design and optimization
  15. Medical chatbots and virtual assistants
  16. Telemedicine and remote patient monitoring
  17. Health monitoring wearables and sensors
  18. Predictive modeling for patient deterioration
  19. Surgical planning and simulation
  20. Robot-assisted surgery
  21. Prosthetics and orthotics design
  22. Rehabilitation and physical therapy
  23. Health behavior monitoring and intervention
  24. Medical fraud detection and prevention
  25. Patient sentiment analysis
  26. Mental health assessment and support
  27. Sleep disorder analysis and management
  28. Emergency room triage and resource allocation
  29. Chronic disease management
  30. Predictive analytics for hospital readmissions
  31. Population health management
  32. Public health surveillance and outbreak prediction
  33. Precision medicine and targeted therapies
  34. Clinical trial participant recruitment and matching
  35. Health informatics and data interoperability
  36. Medication adherence monitoring and reminders
  37. Drug dosage optimization
  38. Radiomics and radiogenomics
  39. Medical billing and coding automation
  40. Healthcare resource allocation and optimization
  41. Clinical workflow optimization
  42. Hospital bed management and patient flow
  43. Medical supply chain management
  44. Health chatbots for health education and awareness
  45. Digital therapeutics and mobile health applications
  46. AI-guided genetic counseling
  47. Oncology treatment planning
  48. Medical education and training simulations
  49. Pharmacovigilance and adverse event monitoring
  50. Medical research data analysis and interpretation