Augmenting Community Diagnosis of Safe Ear Disease Through Tele-Myringoscopy with Borescope Using AIML Tecniques.

This study utilized AIML (artificial intelligence & machine learning) techniques to analyze 115 images of central perforation of tympanic membrane obtained from Telemyringoscopy through Borescope in order to establish a facilitation-model for the community ear diagnosis. The Modified VGG19 with batch normalization revealed the highest training accuracy of 85 as compared to other CNN techniques. The training accuracy started to saturate around mid-70% and the Test accuracy was around 50%.

Customized wire prosthesis (Devise) for alar collapse in sleep apnoea.

Background: Alar collapse is known to aggravate snoring-severity and possibly the severity of obstructive sleep apnoea. Various surgical techniques, implants and commercial mechanical/prosthetic nasal alar dilators are evident in literature.

Material And Methods: A malleable wire prosthesis at 'no' manufacturing cost is custom designed through computer modelling and animation and thereafter tested for its efficacy in 20 normal subjects as per visual analog scale along with its correlation with patient-profiles.

Internet-Based Hearing Assessment During COVID era in Indian Population: Practical and Safe Option.

This pilot observation intends to stress on web-based hearing assessment (WBHA) as somewhat parallel to clinical pure tone audiometry. While WBHA was comparable with PTA in context of severity of deafness particularly in symmetrical hearing loss, it was inconclusive for a gross asymmetry despite multiple trials. With increasing COVID transmission, more need for social distancing and lack of audiologists in developing countries, the self-participation by patients in WBHA model will prove to be a very safe model of deafness-screening.

Enhancing India's Health Care during COVID Era: Role of Artificial Intelligence and Algorithms.

Computerization of health care is the only model to sustain safe health care in this COVID era particularly in overpopulated nations with limited health care providers/systems like India. Accordingly incorporation of computer-based algorithms and artificial intelligence seems very robust and practical models to assist the physician. The advantages of Computerized algorithms to facilitate better screening, diagnosis or follow-up and use of Artificial Intelligence (AI) to aid in medical diagnosis are discussed.

Computer Algorithms in Assessment of Obstructive Sleep Apnoea Syndrome and Its Application in Estimating Prevalence of Sleep Related Disorders in Population.

The incorporation of telemedicine and artificial intelligence for early screening and assessment of severity of life-style disorders has a great potential for better assessment in a busy outpatient clinic and thereby curtail down the related morbidities. A computer based algorithm based upon standardized questionnaire (from established assessment tools) is designed to assess the risk of obstructive sleep apnoea syndrome (OSAS). In addition the incorporation of basic screening questions of anamnesis help in suggesting a probable diagnosis of sleep related disorder as well.