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Coronavirus - COVID-19 - AI and Big Data for containment, diagnostic and treatment

COVID-19: AI and Big Data for Treatment, Containment, and Flattening the Curve

As of April 20, there are 2,440,528 confirmed coronavirus cases and 167,592 deaths globally. Currently, the U.S. continues as the hardest-hit country in the world, with 749,666 total cases – 238,831 of which are in the current epicenter, New York. In deciding timelines for reopening economies, officials from affected countries, including Italy, Spain, China, and the U.S., are relying on AI/ML-powered predictive models to determine next best actions. Given the unpredictability and rapidly-changing pandemic climate, AI/ML is necessary to overcome COVID-19 eventually.

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Role of AI in Patient Adherence

The Role AI Is Playing In Healthcare Patient Adherence

As per a systemic review1 published in Annals of Internal Medicine, assessing the impact of interventions to improve adherence, it was found that about half the medications prescribed for chronic diseases are not consumed as directed by the physician, and around 20-30% of prescriptions are never fulfilled. This non-adherence results in over 125,000 deaths every year as well as increased emergency department visits and hospitalizations, which costs the American healthcare system to the tune of $100 to $300 billion1.

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How Healthcare AI Chatbots Are Transforming the Patient Journey

How Healthcare AI Chatbots Are Transforming the Patient Journey

“Hi Caroline, this is Jeff! You reported feeling heavily symptomatic yesterday. I wanted to see if you are doing better. On a scale from 1-10, how would you rate your pain today?”

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Enabling AI in companies, The Jack Welch way!

Today more than any other day, having started my career in a GE company (the erstwhile GE Capital International Services), I have this involuntary urge to pay my tribute to “Neutron Jack” in my small and perhaps largely insignificant way. But yet, I must, as the words come out, “Straight from the Gut” for the big man, who has left an indelible mark on every individual that he has remotely touched through his rich legacy, leadership, and philosophy.

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Three Rare Disease Diagnoses Opportunities For AI and Machine Learning

Three Rare Disease Diagnoses Opportunities For AI and Machine Learning

The world of health and medicine has broken countless barriers over the last few scores. Life sciences companies have continued to invest significantly in their research of globally corroding diseases, drug molecules discovery and development, and closely monitored clinical trials, to create industry-approved blockbuster medicines. These drugs, gaining precision with time, are curing more diseases and giving patients a chance at better lives. The pharma journey, however, gets complicated with more in-depth clinical and genetic research, as companies continue to find themselves facing more significant ‘unknowns’ than ever before.

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Life Sciences Tech Trends 2020

2020 Emerging Technology Trends in the Life Sciences Industry

The life sciences industry has always been propelled by research and innovation, more now than ever, with breakthrough drug development, massive investments to expedite drug launches, and opportunities for medical advancements. To put this into perspective, let’s consider the clinical development trends for the last ten years. There were more than 16,0001 assets in clinical development in 2019, and almost 1,7002 investigational new drug applications (INDs) were filed, up from 9,700 drugs in clinical development, and 1,300 INDs filed in 20103. Along with substantial investments in drug discovery and research and development, life sciences companies are also transforming in the areas of data management, business intelligence, and analytical capabilities by adopting digital transformation, artificial intelligence (AI), machine learning (ML), NLP (Natural Processing Language), and most pertinently, automation.

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Artificial Intelligence in Healthcare Books

The Essential Artificial Intelligence in Healthcare Book Giving Guide

Do you have a bookworm or someone who loves to learn on your gift list? Perhaps someone interested in how artificial intelligence (AI) and machine learning (ML) are breaking the traditional barriers in healthcare? Or, maybe you want to grab a hot cup of cocoa and a book on how AI is impacting healthcare to busy your mind on a cold winter day.

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Four Pillars Of The Fourth Industrial Revolution for Life Sciences

Data and technology are etching a new DNA of each touchpoint of our lives today. As we live and breathe, the fourth industrial revolution and its fusion of technologies are dissolving the boundaries of physical, digital, and biological spheres1. As humans, we are more connected than ever before, using extremely advanced technologies, creating unbelievable amounts of extremely granular data. This data explosion is feeding into AI-based quantum computing engines for instant and highly-personalized insights, which help us make better decisions. To operationalize our informed decisions, Internet of Things (IoT) and its connected experience step in to deliver instantaneous desired results. As customers, we are embracing these advancements towards elite customer experiences. As professionals, we need to follow suit, by leveraging data and technology to create innovative products, operational efficiencies, stronger customer equity, and higher profit margins.

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Driver Score - Quantifying your Moves

With the advancements in the field of science and technology, more and more appliances have integrated systems capable of storing and reporting streams of data. Under the field of telematics, various devices are being used to extract, store and transform information related to vehicles and their usage. The data provided by these devices also contains information regarding various aspects of the driver including the driving patterns.

Need of an hour is the unified rating for drivers that represents how good a driver is, irrespective of the device or telematics service provider (TSP). A lot of information related to driving behaviors is being tracked through in-vehicle telecommunication devices (telematics) that are usually self-installed into a special vehicle port and can be used to predict the level of risk that a driver will cause an accident in foreseeable future. Through this paper, we propose the following methodology to calculate these rating, the driver scores as it is generally called.

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