Healthcare

Attention Mechanism: Benefits and Applications

Recurrent Neural Networks (RNNs) are powerful neural network architectures used for modeling sequences. LSTM (Long Short Term Memory) based RNNs are surprisingly good at capturing long-term dependencies in the sequences. A barebones sequence-to-sequence/encoder-decoder architecture performs incredibly well in tasks like Machine Translation. A typical sequence-sequence architecture consists of an encoder and a decoder RNN. The…

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Blockchain in Drug Discovery and Development

The uses and application of blockchain technology are vast and far-reaching. In this article, Tushar Sinkar explores some blockchain uses that can be applied for drug discovery and development, such as eliminating data tampering and ensuring IP protection, among other uses.

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Privacy and Machine Learning: Concerns and Possible Solutions

AI and its applications are here to stay, even if they bring with them new challenges, as their advantages seem to outweigh the risks. However, in the light of latest controversies and concerns over privacy breach by social companies, the efforts to ensure privacy of users need to be redoubled. Arjun Bahuguna discusses the solutions that manage the vulnerabilities of machine learning and instead leverages its strength to guard information privacy.

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Women and Data Science

It is well-known that there are far fewer women techies and those that do choose work in tech, somehow avoid data science. Archana Iyer discusses the merits of having more women in the field of data science and presents some reasons why she feels that women’s innate temperament is highly suited to data science.

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Blockchain Smart Contract Security

Blockchain is a digital ledger in which cryptocurrency transactions are recorded. In this article, Arjun Bahuguna discusses ethereum, a public blockchain, as it is the most popular platform for writing smart contracts and building decentralized applications.

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Quantization and the Need for TPUs

Archana dives into the world of TPUs and discusses quantization, the process that is really responsible for making predictions in a neural network, lending a magical touch to the machine learning process. Read on to understand how quantization can be both a boon and a bane, depending on where it is used.

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Analytics Trends 2018: Blockchain and AI to Accelerate Clinical Trials Transformation

All clinical trial processes are witnessing rapid transformation due to the demand for faster and completion of trials at lower costs. Insights gleaned from Real World Data (RWD) in the past few years have offered several avenues for improving clinical trials. Sagar Anisingaraju discusses the upcoming trends of 2018 in this light. Read on to learn about the technologies poised to make a wave this year.

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An Attentive Sequence Model for Adverse Drug Event Extraction from Biomedical Text

Adverse reaction caused by drugs is a potentially dangerous problem which may lead to mortality and morbidity in patients. Adverse Drug Event (ADE) extraction is a significant problem in biomedical research. We model ADE extraction as a Question-Answering problem and take inspiration from Machine Reading Comprehension (MRC) literature, to design our model. Our objective in…

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