Publications by authors named "O Sumer"
Blueprint of a pandemic: Insights from SARS-CoV-2 genomics surveillance in Meghalaya, India.
Diagn Microbiol Infect Dis
December 2024
The Covid-19 pandemic uncovered several lacunae in healthcare systems exposing global unpreparedness and triggering unprecedented challenges worldwide- necessitating a shift towards mitigation and robust surveillance strategies. Here, we report the use of Whole Genome Sequencing (WGS) to detect SARS-CoV-2 variants in clinical samples of Meghalaya, India, using Oxford Nanopore Technology. SARS-CoV-2 positive samples collected from various districts of Meghalaya from August 2021 to May 2023 were subjected to WGS.
View Article and Find Full Text PDFArtificial intelligence (AI) is increasingly used in genomics research and practice, and generative AI has garnered significant recent attention. In clinical applications of generative AI, aspects of the underlying datasets can impact results, and confounders should be studied and mitigated. One example involves the facial expressions of people with genetic conditions.
View Article and Find Full Text PDFArticle Synopsis
- AI for facial diagnostics is being used in genetics clinics to identify potential genetic conditions, primarily through Deep Learning (DL) technologies, which show high accuracy for many disorders.
- A study comparing eye-tracking of geneticists and non-clinicians revealed significant differences in how humans and DL models focus on images of individuals with genetic conditions, with notable discrepancies in visual attention patterns.
- The findings suggest that better understanding of these differences can enhance the development and implementation of AI tools in clinical settings, fostering improved integration between clinicians and AI technologies.
Article Synopsis
- - Deep learning and AI are being applied in medical genetics, particularly for diagnosing potential genetic conditions using image evaluations.
- - A study was conducted to compare how geneticist clinicians and non-clinicians visually assess these images, using eye-tracking analyses and DL-based saliency maps for comparison.
- - Results indicated significant differences in visual attention between humans and the DL model, with clinicians and non-clinicians showing distinct patterns in their image inspection.
Few-Shot Meta-Learning for Recognizing Facial Phenotypes of Genetic Disorders.
Stud Health Technol Inform
May 2023
Computer vision has useful applications in precision medicine and recognizing facial phenotypes of genetic disorders is one of them. Many genetic disorders are known to affect faces' visual appearance and geometry. Automated classification and similarity retrieval aid physicians in decision-making to diagnose possible genetic conditions as early as possible.
View Article and Find Full Text PDF