What Does the Future Hold for AI in Healthcare?

Aditya Chakurkar | December 17, 2021 | 26 views

What_Does_the
The Covid-19 Pandemic has turned our world upside down and has taken a major toll on almost every aspect of our lives. While it severely impacted things negatively, it also made some positive changes in our society. For instance, it accelerated the digital transformation like never before. As a result, every industry today is more technology-centered. And now, there’s no stopping to this!

For obvious reasons, the healthcare industry is at the center of all industries. Not too long ago, as the contagious coronavirus was killing people around the globe, the healthcare sector was tirelessly working to minimize the damage. During all this hustle and bustle, telehealth became a necessity, and this led to the increased use of artificial intelligence in the medical field.

"The promise of artificial intelligence in medicine is to provide composite, panoramic views of individuals’ medical data; to improve decision making; to avoid errors such as misdiagnosis and unnecessary procedures; to help in the ordering and interpretation of appropriate tests; and to recommend treatment."

Eric Topol, Deep Medicine: How Artificial Intelligence Can Make Healthcare Human Again


In recent months, the role of artificial intelligence in the medical field has been one of the hottest talking points, and the adoption of this tech is not showing any signs of slowing down. As AI can make medical care more human with improved accuracy and efficiency, the healthcare industry is counting on AI healthcare applications for making better decisions, managing patient data, developing customized medicine plans, discovering new drugs, and much more.

Here are some common use cases of artificial intelligence in the medical field.

Current Examples of Artificial Intelligence in the Medical Field

Most of the current AI healthcare applications revolve around NLP (natural language processing), RPA (robotic process automation), and pattern recognition. The following are well-known examples of how artificial intelligence is used in healthcare.


Primary Healthcare

AI is a transformational force when it comes to primary care. With millions of annual patient visits in the US alone, primary care has the biggest need for AI implementation to ease the burden. The following are the major primary care areas where AI is already generating amazing advantages:

  • Medical advice and triage
  • Medical diagnosis
  • Risk prevention
  • Risk interventions
  • Coaching for digital health
  • Managing medical practice
  • Clinical decision-making
  • Resourcing and paneling

 

"We should think about AI the way we think about patient care — as a continuum, spanning care areas and disease states.”

Dr. Mark Michalski, Executive Director of MGH and BWH Center for Clinical Data Science


Risk Management

According to the data from Health Leaders Media, the total expenditure on potentially preventable medical conditions is $1 out of every $10. With accurate risk management, hospitals can save billions of dollars.

A real-time example of this is the AI-powered BaseHealth technology implemented by Banner Health in Phoenix, Az. It carries out primary care interventions and helps the hospital management predict around 42 medical conditions. This reduces emergency room utilization to a great extent.


Drug Development & Discovery

Discovering new drugs and taking them to market is a lengthy and troubling process. In a study conducted by BIO (Biotechnology Innovation Organization), it was found that 9 out of 10 clinical drugs don’t make it to the trials and even fewer reach the FDA approval stage. This drives the cost of drug discovery and development to a very high level and unfortunately, these costs are often passed down to ordinary people.

Thankfully, AI can be used to slice down the expenditure required in the R&D of drugs with effective drug discovery, development and even marketing. The biggest example of this is the collaboration of Toronto-based biotech firm Cyclica and Bayer AI to arm pharma operations with AI and cloud platforms to improve the overall efficiency of drug R&D.


Radiology

CAD (computed aided detection) was the first AI-powered tool used in radiology. Today, AI has come a long way in the radiology field and offers several benefits to radiologists. The following are the AI healthcare applications for radiologists:

  • Hidden fracture detection
  • Neurological abnormalities detection
  • Breast cancer detection
  • Brain tumor classification

Furthermore, AI algorithms can help radiologists offer a second opinion. New York-based Mount Sinai Health System utilized AI medical diagnosis alongside a human expert as another option for a second opinion for novel coronavirus detection.


Future of AI in Healthcare

The amount of research on artificial intelligence in the medical field is increasing rapidly. The following are the (at least) predictions as to which trends will be the hottest trends when it comes to future AI in the healthcare space.


Medical Diagnosis of AI

Diagnosis prediction is one of the key areas that will experience AI’s forceful impacts. Machine learning models in the future will enable AI medical predictions to predict medical conditions at their onsets or much before they actually exhibit themselves.


Telemedicine

Thanks to machine learning-based models, in the future, people will be able to receive hospital-like treatments in the comfort of their homes. There will be advanced versions of AI chatbots that will be able to provide medical guidance to patients and also receive information from them about their symptoms.


Electronic Health Records (EHR)

Even though electronic health records are not completely related to artificial intelligence, they have a critical share in AI’s role in healthcare in the future. EHRs are nothing but the digital version of doctors’ notes about the patient. It has data related to patients' 10-year medical history, health journey, and diagnoses. In a way, they are huge databases that can be used with AI and Machine Learning techniques to extract and gather critical patient data.


Wrapping Up

In a nutshell, healthcare is one of the most important sectors that artificial intelligence will undoubtedly revolutionize. The industry is already set to invest trillions of dollars in collaboration with AI, which clearly indicates the level of impact AI will have on the healthcare universe.


Frequently Asked Questions


What are the most common challenges to applying artificial intelligence in the medical field?

Appropriate strategies are necessary to overcome the following common challenges you may face while applying AI in the medical field:

  • Identifying potential use cases
  • Training staff and patients
  • Collecting data
  • Compliance maintenance
  • Getting rid of the black box


What are the key benefits of AI in healthcare?

Doctors and patients agree that artificial intelligence is beneficial. The following are the key benefits of AI in healthcare:

  • Enhancing healthcare accessibility
  • Operational efficiency
  • Optimized  performance
  • Accurate clinical decision-making


Which ethical dilemmas do you encounter while applying AI in healthcare?

The following are the ethical and legal dilemmas you need to think about when applying AI to healthcare:

  • Algorithmic fairness
  • Data privacy
  • Cybersecurity
  • Liability
  • Consent to use
  • Patient safety

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GENERAL AI

SoftWorks AI Rebrands as TRUE and Answers Need for Lending Intelligence

TRUE | June 23, 2022

SoftWorks AI, the leader in lending intelligence, today launched an extensive rebrand, including changing its name to TRUE. The new name reflects the company’s unique ability to give lenders a true picture of a borrower by using AI to inspect and audit every data point when verifying a loan and its underlying documentation. By providing deeper, more comprehensive, and more accurate insights on borrowers, TRUE allows lenders to gain market share by enabling faster turn times and reducing risk. TRUE’s new name and logo demonstrate how the company harnesses the power of AI to turn lending – especially in the mortgage space – into a near real-time experience. While other vendors need humans in the loop to get data right, TRUE’s platform accurately analyzes every data point in a loan package automatically. TRUE’s technology can reduce manual reviews by up to 85% and has increased underwriter productivity by up to 300%. The lending industry has long been focused on automation, with an end-state goal of touchless automation. This can only be achieved with lending intelligence, which uses AI to ensure all data going into the automation process is 100% correct and verify that every extrapolated insight is accurate and provably true. The TRUE brand is focused on using cutting-edge technology to find what is true, a process the company calls Lending Intelligence. “TRUE uses AI to help lenders address customers’ most important expectations – speed, accuracy and reduced risk. “We are an AI lab focused executively on the lending sector and our AI platform is fully trained to address the challenges and nuances of lending. TRUE optimizes every step of the lending cycle, efficiently delivering critical information so our clients can get a full picture of their risk exposure. By providing a fast, thorough, and explainable analysis of every last data point, we reduce errors and improve decisioning, powering trustworthy lending.” Ari Gross, CEO of TRUE TRUE is transforming both the primary and secondary lending markets with technology that reads documents chronologically and holistically, going far beyond generic data classification that misses important details and nuances – and results in costly bad decisions. By ensuring that loan documents tell a consistent and coherent story and that all documents are cross-validated, TRUE enables lenders to get a holistic view of lending risk while delivering greater certainty to customers. The company currently serves major institutions from across the lending industry including Rocket Mortgage, Carrington, and 50% of the top mortgage insurers. TRUE processes millions of loans and billions of documents through its AI powered lending technology annually. About TRUE TRUE is a software solutions company and AI lab that helps lenders harness the power of artificial intelligence to make accurately informed lending decisions – increasing revenue while reducing operating costs and risk. Since 2017, it has set the industry standard for intelligent lending technology, delivering results that provide a true competitive advantage.

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GENERAL AI

AI Quality Leader TruEra Receives Investment from Hewlett Packard Enterprise

TruEra | June 23, 2022

Hewlett Packard Enterprise announced today that it has invested in TruEra through its venture capital program, Hewlett Packard Pathfinder. TruEra offers the first suite of AI Quality management solutions for managing model performance, explainability, and societal effect. The $25M Series B round TruEra announced in March 2022 is now extended. Hewlett Packard Pathfinder invests in market-leading start-ups, develops solutions fusing the technology of portfolio companies with Hewlett Packard Enterprise goods, and designs collaborative go-to-market strategies. Hewlett Packard Pathfinder also keeps a careful eye on longer-term disruptive innovation, supporting the development of cutting-edge technology. "We're excited to become an investor and to partner with TruEra in developing comprehensive solutions for our enterprise customers in conjunction with our High-Performance Computing offering," said Paul Glaser, Vice President and Head of Hewlett Packard Pathfinder. The quality challenge, the following significant AI challenge, is addressed by TruEra. In order to quickly correct problems and maintain peak performance, ML teams can use TruEra's solutions to explain, analyze, and test the performance, risk, and responsible AI characteristics of models early in the development process. As a result, numerous Fortune 1000 businesses have chosen TruEra as their preferred provider because of its distinctive, whole lifecycle approach to model quality. "AI model quality and ML Ops have emerged as considerable challenges for enterprises deploying and scaling machine learning models. Solving these challenges is imperative for AI success, and TruEra stands out for its deep expertise, differentiated technology and practical experience helping companies deliver and monitor AI applications." Ali Wasti, Managing Director, Hewlett Packard Pathfinder Top-tier investors such as Menlo Ventures, Greylock Partners, and Wing Venture Capital have contributed approximately $45 MM to TruEra. Anupam Datta and Shayak Sen, co-founders of TruEra, conducted academic research at Carnegie Mellon University that served as the basis for the company's technology. "Hewlett Packard Enterprise is a leading, trusted provider to the enterprise, and is known for its ability to ensure that cutting-edge innovation delivers proven results. We're looking forward to working closely with the HPE team as partners on customer engagements," said Will Uppington, CEO and co-founder, TruEra.

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