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Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.
That’s great news for researchers who often work on SLRs because the traditional process is mind-numbingly slow: An analysis from 2017 found that SLRs take, on average, 67 weeks to produce. As the capabilities of high-powered computers and ML algorithms have grown, so have opportunities to improve the SLR process. dollars apiece.
Machine learning algorithms can also recognize patterns in DNA sequences and predict a patient’s probability of developing an illness. These algorithms can design potential drug therapies, identify genetic causes of disease, and help understand the mechanisms underlying gene expression.
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