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.

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.

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.

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?

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.

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.

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.

A great trainer makes working out 10x more motivating, fun, and effective. That's why we created Vi--an evolving personal trainer who lives in bio-sensing earphones. Put Vi on and start a relationship with a friend for your fitness. Each day, Vi tracks you, gets smarter, and coaches you to real results. Vi will help you meet your weight goals, improve your running, cycling and training.

Data is rarely clean and often you can have corrupt or missing values. It is important to identify, mark and handle missing data when developing machine learning models in order to get the very best performance. In this post you will discover how to handle missing values in your machine learning data using Weka. How To Handle Missing Data For Machine Learning in Weka Photo by Peter Sitte, some rights reserved. The problem used for this example is the Pima Indians onset of diabetes dataset.

I just finished the book The Art of Happiness by the Dalai Lama and Howard Cutler. And while I got a great deal of personal wisdom from the book, I also found that the Buddhist philosophy of cultivating compassion and empathy to be an interesting angle to machine ethics and artificial intelligence design. The premise of one of the chapters is that human nature is essentially compassionate and gentle at birth and that anger, violence, and aggression are the result of the unbalanced development or misuse of our intelligence. Intelligence, the same intelligence that has allowed us to be masters of this world, that's not counterbalanced with compassion can become destructive. The way we are constructing our AI projects is starting with the intelligence.