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Released in 2020, AlphaFold leverages deep learning algorithms to accurately predict the 3D structure of proteins from their amino acid sequences, outperforming traditional methods by a significant margin.
NaturalLanguageProcessing Getting desirable data out of published reports and clinical trials and into systematic literature reviews (SLRs) — a process known as data extraction — is just one of a series of incredibly time-consuming, repetitive, and potentially error-prone steps involved in creating SLRs and meta-analyses.
Charting the evolution of SOTA (State-of-the-art) techniques in NLP (NaturalLanguageProcessing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.
Figure 1: Global Funding in Health Tech Companies (source: Mrazek and O’Neill, 2020 ). Machine learning algorithms can also recognize patterns in DNA sequences and predict a patient’s probability of developing an illness. Accenture estimates that the health AI market in the United States is expected to grow at 40% annually.
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