Vol. 2 No. 3 (2024): Volume-II, Number-III, 2024
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Predicting the Future How Deep Learning is Revolutionizing Stem Cell Therapy Outcomes
Abstract 51
Regenerating therapy using stem cells has proved to be a future area of regenerative medicine which can cure people of degenerative disorders, damage to organs and chronic diseases. Nevertheless, it is a significant challenge to know the therapeutic outcomes because of the occurrence of variability in patients, protracted cell differentiation pathways, and spontaneously unfixed immune completio ... read more
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Integrating Deep Learning with Single-Cell Transcriptomics for Predictive Modeling in Stem Cell Therapy
Abstract 40
Stem cell therapy has tremendous potential to treat a broad range of medical conditions, but technical aspects of this therapeutic approach have hampered its clinical application because differentiation outcomes can be unpredictable, cellular heterogeneity is not fully understood, and predictions of the efficacy of stem cell therapy are cumbersome. Single-cell transcriptomics (scRNA-seq) techno ... read more
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Quantum Neural Networks the Next Leap in Artificial Intelligence
Abstract 54
One of the most promising new directions in quantum computing and artificial intelligence convergence is the Quantum Neural Networks (QNNs) that can potentially revolutionize the manner in which intelligent systems are designed, trained, and implemented. Although traditional deep learning models have proven to be incredibly successful in fields like computer vision, natural language processing ... read more
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Post-Quantum Cryptography Preparing for the Quantum Threat to Digital Security
Abstract 52
The impressively fast development of quantum computing is a serious threat to classical public-key cryptography, and algorithms such as Shor's and Grover's will render RSA and elliptic curve systems essentially useless as soon as a cryptanalytically relevant quantum computer becomes available. Although it is still some way off before such machines are available, the harvest-now-encrypt-later th ... read more
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Advancements in Cybersecurity: Leveraging AI and Machine Learning for Threat Detection and Prevention
Abstract 44
This paper explores the transformative role of Artificial Intelligence (AI) and Machine Learning (ML) in advancing cybersecurity through enhanced threat detection and prevention techniques. AI and ML technologies have become pivotal in addressing the ever-evolving landscape of cyber threats, providing dynamic solutions for identifying, analyzing, and mitigating risks. By leveraging pattern reco ... read more