Publications by authors named "V Masilamani"
We are writing to address the growing interest in the role of artificial intelligence (AI) within healthcare, particularly in the field of reproductive health. As technology continues to evolve, AI offers an unprecedented opportunity to transform how we diagnose, treat, and improve access to reproductive services, especially in underserved communities. AI-driven tools, supported by machine learning and big data analytics, are already demonstrating their potential in enhancing outcomes in reproductive health.
View Article and Find Full Text PDFcomplications, infectious diseases, maternal and infant health in disasters, gender-based violence, healthcare access inequities, mental health impacts, and food security issues. Findings reveal an uneven distribution of coverage across continents, with potential language bias in English-dominated sources. Acknowledging limitations, future research directions emphasize a more inclusive approach, incorporating diverse linguistic perspectives and qualitative exploration of community experiences.
View Article and Find Full Text PDFArticle Synopsis
- Researchers are now using Artificial Intelligence (AI) not just to find but also to help treat diseases, especially when it comes to making new medicines.
- A big concern in drug development is predicting Adverse Drug Reactions (ADRs), which are harmful effects that drugs can cause, as they can sometimes be serious or even deadly.
- The new method presented uses something called Knowledge Graphs to train a special type of AI model named KGDNN to better predict these ADRs, showing much better results than previous methods.
SARS-CoV-2, hemoglobin and protoporphyrin IX: Interactions and perspectives.
Photodiagnosis Photodyn Ther
June 2021
Background: SARS-CoV-2 attacks hemoglobin through its structural protein ORF3a, dissociating the iron from the heme, as iron is necessary by cell machinery for virus replication. In this process protoporphyrin (PpIX) is released.
Methods: The decrease in the hemoglobin levels observed in patients with Covid-19 is frequently accompanied by an increase in PpIX levels.
Spectral diagnostic screening for sickle cell disease was carried out on volunteer blood samples (N = 100). The samples were subjected to different diagnostic methods including conventional complete blood count (CBC), hemoglobin electrophoresis (HBE) and spectral diagnosis. For the spectral diagnostic method, we discriminated three different characteristic spectral features.
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