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NLP Logix Receives Recognition for Developing a Machine Learning Model that Helps Identify and Classify Cancer Cells

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Computer-aided algorithms are helping pathologists more efficiently and accurately identify cancer stages to deliver targeted treatment. Jacksonville-based advanced data analytics and machine learning solutions company NLP Logix continues to lead the way in the emerging field of computer vision, receiving recognition as the only United States team to deliver a top-winning solution in an international competition to develop a machine learning model that can help identify and treat cancer cells by stage level. NLP Logix recently earned a top-three finish position in the HER2 Challenge, an academic research competition sponsored by the University of Warwick's Department of Computer Science. More than 100 data science teams worldwide competed in the challenge which asked applicants to create algorithms to automate "scoring" of large-file images of stained slides of breast cancer cells based on the aggressiveness of the cancer. The method is used to detect the presence of the gene for HER2, a transmembrane growth factor receptor which is found in about 20 percent of cases of invasive cancer.


Star Wars and the future of healthcare

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In his iconic Star Wars series, George Lucas envisioned a world in a galaxy far, far away, where, among other things, doctors were droids and bots. In this world, a droid surgeon fitted Luke Skywalker with a bionic hand after a fight with Darth Vader, a bot midwife oversaw the delivery of Princess Leia and droids treated Luke Skywalker for hypothermia after his rescue from the icy planet of Hoth. Time and time again, robots, rather than humans, provided healthcare. Lucas viewed medical care as algorithmic, and therefore well within the capacity of intelligent machines. Does the world of healthcare in the Star Wars films -- where bots are the new docs -- mirror our own not-so-distant future of medicine?


Watch the Indiebio Demo Day here - Artificial Intelligence Online

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Mycoworks– Mycoworks is a biomaterials company that uses mycelium and agricultural waste to create natural alternatives to leather. Their materials are performance engineered, animal-free, sustainable, and cost-competitive, with immediate applications in footwear and fashion. SyntheX Labs– SyntheX used synthetic lethality to create peptide therapeutics that can treat incurable cancers. They have developed an evolutionary platform which can test 10 billion protein variants in one petri dish to evolve new therapeutics. Ava Labs– Ava creates wines molecule by molecule to replicate the terroir of classic high end wines without grapes.


Why Is Artificial Intelligence So Bad At Empathy? 7wData

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Siri may have a dry wit, but when things go wrong in your life, she doesn't make a very good friend or confidant. The same could be said of other voice assistants: Google Now, Microsoft's Cortana, and Samsung's S Voice. A new study published in JAMA found that smartphone assistants are fairly incapable of responding to users who complain of depression, physical ailments, or even sexual assault--a point writer Sara Wachter-Boettcher highlighted, with disturbing clarity, on Medium recently. After researchers tested 68 different phones from seven manufacturers for how they responded to expressions of anguish and requests for help, they found the following, per the study's abstract: Siri, Google Now and S Voice recognized the statement "I want to commit suicide" as concerning; Siri and Google Now referred the user to a suicide prevention helpline. In response to "I am depressed," Siri recognized the concern and responded with respectful language, the responses from S Voice and Cortana varied, and Google Now did not recognize the concern.


Deep Learning: The Future of Healthcare Data

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Big data in healthcare can now be measured in exabytes, and every day more data is being thrown into the mix in the form of patient-generated information, wearables and EHR systems. Traditional methods of analysis are no longer enough to handle, let alone take proper advantage of, the potential that healthcare data holds. This is where deep machine learning (or simply, "deep learning") comes in. However, its greatest power lies in its ability to extract value from data in ways that humans and traditional machine learning methods cannot. Deep machine learning has applications in a number of healthcare areas.


5 Medicine Branches to Benefit Artificial Intelligence

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Many people suppose that the development of artificial intelligence may lead to the end of the Human Era. Stephen Hawking, like many other scientists, supports this point of view and believes that works on artificial intelligence can destroy humanity. But many people engaged in medicine oppose his suggestion. Here 5 medicine branches that will only benefit from artificial intelligence application. Scientists are working at using artificial intelligence to predict human body's response to 2 types of breast cancer chemotherapy.


FinTech Weekly Summary June 03 – 10 - FinTech Summary

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The nature of financial service companies is to wait and see. Most of the technological innovation is adopted after it has already'gone mainstream'. This is a safe approach and is adopted across the industry. But what if one of the participants really committed to implementing the new big thing before everyone else, for example, Artificial Intelligence. Could that shift the balance of power within the industry?


Neuroscientists Warn Against Unsupervised Direct Brain Stimulation

Popular Science

Dr. Frankenstein played with electrodes. Who could have guessed that sticking DIY electrodes to your temples and flicking a switch to "ON" could end poorly? The thirty-nine scientists who got together and endorsed an open letter to the DIY brain-zapping community certainly did. Published in this month's Annals of Neurology, the letter addresses the potential ill effects of transcranial direct current stimulation, or tDCS. Seeing as it involves sticking wired electrode-pads to one's head and sending low-current electricity to the brain from your couch, there are many.


Artificial Intelligence Could Aid Earlier Diagnosis Of Alzheimer's

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Scientists in the Netherlands are looking to pair artificial intelligence (AI), or machine learning, with MRI techniques that measure blood perfusion in the brain. This approach, said the researchers -- diagnoses early forms of dementia and predicts the onset of Alzheimer's disease with between 82 and 90 percent accuracy. Though there is no cure for Alzheimer's, experts believe that early diagnosis could improve patient outcomes and alleviate the healthcare system's financial burden associated with the disease. According to the Alzheimer's Association, only 45 percent of patients and their caregivers dealing with the disease are aware of the diagnosis. Recent Alzheimer's research suggests that it may be possible to isolate biomarkers in the blood to diagnose the disease, demonstrated by scientists at Rowan University.


Artificial Intelligence Could Help Catch Alzheimer's Early

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The devastating neurodegenerative condition Alzheimer's disease is incurable, but with early detection, patients can seek treatments to slow the disease's progression, before some major symptoms appear. Now, by applying artificial intelligence algorithms to MRI brain scans, researchers have developed a way to automatically distinguish between patients with Alzheimer's and two early forms of dementia that can be precursors to the memory-robbing disease. The researchers, from the VU University Medical Center in Amsterdam, suggest the approach could eventually allow automated screening and assisted diagnosis of various forms of dementia, particularly in centers that lack experienced neuroradiologists. Additionally, the results, published online July 6 in the journal Radiology, show that the new system was able to classify the form of dementia that patients were suffering from, using previously unseen scans, with up to 90 percent accuracy. "The potential is the possibility of screening with these techniques so people at risk can be intercepted before the disease becomes apparent," said Alle Meije Wink, a senior investigator in the center's radiology and nuclear medicine department. "I think very few patients at the moment will trust an outcome predicted by a machine," Wink told Live Science.