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Surgical Robots, New Medicines and Better Care: 32 Examples of AI in Healthcare
Artificial intelligence simplifies the lives of patients, doctors and hospital administrators by performing tasks that are typically done by humans, but in less time and at a fraction of the cost. One of the world's highest-growth industries, the AI sector was valued at about $600 million in 2014 and is projected to reach a $150 billion by 2026.
Whether it's used to find new links between genetic codes or to drive surgery-assisting robots, artificial intelligence is reinventing — and reinvigorating — modern healthcare through machines that can predict, comprehend, learn and act.
The company’s deep learning platform analyzes unstructured medical data (radiology images, blood tests, EKGs, genomics, patient medical history) to give doctors better insight into a patient’s real-time needs.
The scientists used 25,000 images of blood samples to teach the machines how to search for bacteria. The machines then learned how to identify and predict harmful bacteria in blood with 95% accuracy.
Adam scoured billions of data points in public databases to hypothesize about the functions of 19 genes within yeast, predicting 9 new and accurate hypotheses.
BERG recently presented its findings on Parkinson’s Disease treatment — they used AI to find links between chemicals in the human body that were previously unknown — at the Neuroscience 2018 conference.
Location: Cambridge, Massachusetts How it's using AI in healthcare: Combining AI, the cloud and quantum physics, XtalPi’s ID4 platform predicts the chemical and pharmaceutical properties of small-molecule candidates for drug design and development.
Additionally, the company claims its crystal structure prediction technology (aka polymorph prediction) predicts complex molecular systems within days rather than weeks or months.
Atomwise’s AI technology screens between 10 and 20 million genetic compounds each day and can reportedly deliver results 100 times faster than traditional pharmaceutical companies.
Location: London, England How it's using AI in healthcare: The primary goal of BenevolentAI is to get the right treatment to the right patients at the right time by using artificial intelligence to produce a better target selection and provide previously undiscovered insights through deep learning.
A 2016 study of 35,000 physician reviews revealed 96% of patient complaints are about lack of customer service, confusion over paperwork and negative front desk experiences.
New innovations in AI healthcare technology are streamlining the patient experience, helping hospital staff process millions, if not billions of data points, faster and more efficiently.
The company’s technology helps hospitals and clinics manage patient data, clinical history and payment information by using predictive analytics to intervene at critical junctures in the patient care experience.
Location: Cleveland, Ohio How it's using AI in healthcare: The Cleveland Clinic teamed up with IBM to infuse its IT capabilities with artificial intelligence. The world-renowned hospital is using AI to gather information on trillions of administrative and health record data points to streamline the patient experience.
Since implementing the program, the facility has seen a 60% improvement in its ability to admit patients and a 21% increase in patient discharges before noon, resulting in a faster, more positive patient experience.
Additionally, the inability to connect important data points is slows the development of new drugs, preventative medicine and proper diagnosis. Many in healthcare are turning to artificial intelligence as way to stop the data hemorrhaging.
Location: Seattle, Washington How it's using AI in healthcare: KenSci combines big data and artificial intelligence to predict clinical, financial and operational risk by taking data from existing sources to foretell everything from who might get sick to what's driving up a hospital’s healthcare costs.
The company’s software helps pathology labs eliminate bottlenecks in data management and uses AI-powered image analysis to connect data points that support cancer discovery and treatment.
How it's using AI in healthcare: When IBM’s Watson isn’t competing on Jeopardy!, it's helping healthcare professionals harness their data to optimize hospital efficiency, better engage with patients and improve treatment.
Location: Shenzhen, China How it's using AI in healthcare: ICarbonX is using AI and big data to look more closely at human life characteristics in a way they describe as “digital life.' By analyzing the health and actions of human beings in a “carbon cloud,' the company hopes its big data will become so powerful that it can manage all aspects of health.
Robots equipped with cameras, mechanical arms and surgical instruments augment the experience, skill and knowledge of doctors to create a new kind of surgery. Surgeons control the mechanical arms while seated at a computer console while the robot gives the doctor a three dimensional, magnified view of the surgical site that surgeons could not get from relying on their eyes alone.
Being the first robotic surgery assistant approved by the FDA over 18 years ago, the surgical machines feature cameras, robotic arms and surgical tools to aide in minimally invasive procedures.
Under a physician’s control, the tiny robot enters the chest through a small incision, navigates to certain locations of the heart by itself, adheres to the surface of the heart and administers therapy.
Location: Eindhoven, The Netherlands How it's using AI in healthcare: MicroSure’s robots help surgeons overcome their human physical limitations. The company's motion stabilizer system reportedly improves performance and precision during surgical procedures.
Location: Caesarea, Israel How it's using AI in healthcare: Surgeons use the Mazor Robotics' 3D tools to visualize their surgical plans, read images with AI that recognizes anatomical features and perform a more stable and precise spinal operation.
MIT's AI researchers find a new antibiotic in an old drug
Researchers at MIT used a machine-learning algorithm to uncover the potent antibiotic properties hiding within a small-molecule drug that had been explored as a potential diabetes treatment.
And, in the face of growing antibiotic resistance, Collins pointed to the need for new screening methods that could help revitalize the industry’s pipeline for developing new antibiotics, a costly process that has seen few successes in recent decades compared to other pharmaceutical research fields.
While other antibiotics may target the structure of bacterial cell walls or interfere with an infection’s enzyme or protein synthesis activity, this new molecule aims to block the electrochemical gradient that flows across cell membranes and is necessary for maintaining cellular metabolism.
“When you’re dealing with a molecule that likely associates with membrane components, a cell can’t necessarily acquire a single mutation or a couple of mutations to change the chemistry of the outer membrane,” first author Jonathan Stokes, an MIT and Broad Institute postdoc, said to MIT News.
- On Tuesday, April 7, 2020
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