Advancing Medical Research with Natural Language Processing by Jennifer Glenski

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Advancing Medical Research with Natural Language Processing & AI: An Introduction

In today’s increasingly digital world, the intersection of AI and healthcare provides rich opportunities to advance medical research. As a data scientist and AI enthusiast with a decade-long experience, I would like to share a few examples of how AI is not only contributing to public good but also revolutionizing the healthcare sector.

AI For Good in Healthcare

AI is increasingly being leveraged to provide solutions in healthcare, from detecting diseases to analyzing large portfolios of medical research. The promise and potential of AI in healthcare are vast, encompassing a wide range of applications and opportunities to do good in the world.

Case Study: AI & NLP in Medical Research

My experience in developing AI for public good includes working on a project aimed at using natural language processing (NLP) to advance medical research. With millions of clinical studies and medical research papers in various research portfolios, it is beyond human capacity to manually read, categorize, and analyze them in a reasonable timeframe. The solution was an AI and NLP-based tool, which can effectively analyze, summarize, and classify research studies and papers.

Behind the Tech: AI & NLP Tools

  • Pretrained Language Models (PT): Used to understand the meaning of language in text by using the surrounding text as context.
  • Term Frequency Inverse Document Frequency (TF-IDF): Reflects how important a given word is to a document in a collection. Filters out common terms and identifies significant words that can guide research direction.
  • Word Embeddings: Maps words or phrases to a corresponding vector of real numbers, aiding word prediction, similarity calculation, and semantics understanding.

The implementation of this toolset enabled us to identify key trends, novel research opportunities, and gaps in the field of medical research, helping to shape funding policies for the federal government which is a large funder of medical research in the United States.

Other Formidable Examples of AI in Healthcare

The application of AI stretches across various fields in healthcare, of which a few key ones are:

1. Automated Retinal Disease Assessment (ARDA): led by Dr. Lily Peng, uses AI to detect lesions in retina that can cause blindness due to diabetes. It is currently being evaluated in the US and other countries, aiming to make specialized eye care low-access areas more accessible.
2. Massachusetts General Hospital's Partnership with NVIDIA: Implemented AI-powered machines for faster testing and diagnostic capabilities, with the AI models trained on billions of medical images in radiology and pathology to identify diseases.
3. Fitbit's AI Algorithms: Developed to detect signs of Atrial Fibrillation (AF) which can lead to high risk of stroke, blood clot, and heart attack.

A Positive Impact on Patients' Lives with AI

The focus of AI has gradually shifted from optimizing business processes and automating household activities to making a significant impact on the healthcare sector. As AI continues to evolve, the number of ways to use AI in healthcare to tackle global health issues is growing too. There are still many opportunities and areas to be discovered, overall contributing to a positive impact on patients' lives.

In conclusion, the potential of AI in healthcare is immense. With continuous research and development of AI and machine learning technologies, we can expect more groundbreaking applications that will revolutionize the healthcare industry and medical research in the future. Please feel free to connect on LinkedIn for more exciting discussions on the impact of AI in healthcare. Enjoy the rest of your day!


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