Alzheimer's Disease


Study will ask 10,000 New Yorkers to share life's data

Daily Mail

The study leaders aim to recruit 10,000 New Yorkers interested in advancing science by sharing a range of personal information, from cellphone locations and credit-card swipes to blood samples and life-changing events. Researchers hope the results will illuminate the interplay between health, behavior and circumstances, potentially shedding new light on conditions ranging from asthma to Alzheimer's disease. Researchers hope the results will illuminate the interplay between health, behavior and circumstances, potentially shedding new light on conditions ranging from asthma to Alzheimer's disease. Researchers hope the results of The Human Project will illuminate the interplay between health, behavior and circumstances, potentially shedding new light on conditions ranging from asthma to Alzheimer's disease


iPhone app tracks your typing to know if you are depressed

Daily Mail

Researchers have developed an iPhone app that uses Apple's ResearchKit, allowing the technology to track and predict the user's mood and episodes by analyzing their keystrokes BiAffect is specifically designed for iOS and uses Apple's ResearchKit. It uses DeepMood architecture that allows the app to analyze keystroke dynamics data in order to infer the user's mood state using state of the art recurrent neural network (RNN) algorithms. BiAffect uses a DeepMood architecture that allows the app to analyze keystroke dynamics data in order to infer the user's mood state using state of the art recurrent neural network (RNN) algorithms. The idea for BiAffect was sparked after the the researcher' s24-year-old son was diagnosed with bipolar disorder'During a manic episode, people with bipolar disorder exhibit some common behaviors, such as talking really, really fast, with diminished self-control and flight of ideas,' Leow said.


Ethics may be the next challenge for artificial intelligence engineers

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"Consider the fictional robot HAL in '2001: A Space Odyssey,' " said Ken Ford, a computer scientist and founder and CEO of the Florida Institute for Human and Machine Cognition, in Pensacola, which has won awards for its robotics innovations. As the head of the Institute for Human and Machine Cognition, Ford knows a thing or two about robots. For example, for patients with Alzheimer's disease who might be fearful of authority figures, researchers have created a friendly, chatty computer avatar that looks like a dog, Ford said. "Amazon was recently criticized for using artificial intelligence to determine where it would and would not deliver packages," said Shawn Rickenbacker, a New York architect and an Artificial Intelligence Research fellow at Tulane University who teaches the AI and social innovation course, Humans Machines.


What if Your Cellphone Data Can Reveal Whether You Have Alzheimer's?

Slate

While we have recently seen important advancements in machine learning and artificial intelligence, this work has been largely driven by consumer applications, with Google, IBM, Facebook, Microsoft, and Amazon leading the way. These companies have developed deep learning models that achieve near-human performance on certain tasks, even as their workings are largely incomprehensible to human users. Most people use the Amazon Echo without an understanding of the A.I. If your Echo doesn't understand you, you simply repeat the sentence until it does or you give up.


Why exercise is the best medicine for your brain

Los Angeles Times

Exercise seems to beat them all, reducing the risk of Alzheimer's disease or cognitive decline by about 35% to 45%, according to the latest evidence. Heisz's study found that exercise didn't seem to prevent dementia in older people who carried the types of genes that make Alzheimer's more likely. Exercise enhances the release of chemicals known as nerve growth factors that help brain cells function properly, say Teresa Liu-Ambrose, director of the Aging, Mobility and Cognitive Neuroscience Laboratory at the University of British Columbia in Vancouver, Canada. Nerve growth factors probably also help build new brain cells, giving the brain an extra cushion against age-related losses.


Augmenting The Brain Is Set To Pioneer Alzheimer's Treatment Big Cloud Recruitment

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Hype aside, there are companies out there who are focusing on how we can use artificially intelligent applications to improve the human experience, sustain life on our planet and significantly boost the economy. Setting their sights on hacking the brain for medical application, this type of technology will one day be able to be leveraged for improving human intelligence, health, and human-computer interaction. Gathering large data sets on the functionality of the cognitive system will take years of research, not to mention a lot of financial investment. Breakthroughs in areas like neuroprosthesis and enhancing human intelligence have the potential to accelerate scientific discovery not only in other aspects of healthcare, but also general AI, and the evolution of enhanced human intelligence.


What should we do about unbelievably intelligent AI? Ben Ross TEDxMacquarieUniversity

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Embracing artificial intelligence might be the key to finding cures to currently incurable, unpreventable, and unstoppable diseases such as Alzheimer's. Ben Ross explains why computers will inevitably beat brains, what possibilities exist for the application of artificial intelligence, and why we need to start preparing for super intelligent, artificial intelligence now. Ben Ross spent his childhood pulling electronic devices apart but luckily in adulthood he's expanded into building; building technology, specifically. Ben is passionate about the power of automation and artificial intelligence, but his intelligence is all real.


Machine Learning Will Reshape Diagnostic Medicine

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As a result, there is a wealth of data available for training neural networks and for other machine learning techniques. One very recent example of this is an application developed by South Korean researchers at Cheonan Public Health Center and Kyong Hwan Jin at the Korea Advanced Institute of Science and Technology. According to a recent report in MIT Technology Review, Hongyoon Choi and Hwan Jin built a deep convolutional neural network (CNN) that is able to accurately identify people who will develop Alzheimer's disease within three years, based soley on a PET (positron emission tomography) brain scan. Using a dataset of brain images of people with full-blown Alzheimer's, those with mild cognitive impairment (MCI), and those with MCI that subsequently developed Alzheimer's, Hongyoon and Kyong were able to train a CNN that could predict the disease with an accuracy of 84 percent.


Machine Learning Will Reshape Diagnostic Medicine

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According to a recent report in MIT Technology Review, Hongyoon Choi and Hwan Jin built a deep convolutional neural network (CNN) that is able to accurately identify people who will develop Alzheimer's disease within three years, based soley on a PET (positron emission tomography) brain scan. Using a dataset of brain images of people with full-blown Alzheimer's, those with mild cognitive impairment (MCI), and those with MCI that subsequently developed Alzheimer's, Hongyoon and Kyong were able to train a CNN that could predict the disease with an accuracy of 84 percent. The results showed that the all four machine learning algorithms were better at predicting cardiovascular disease than the ACC algorithm, with the neural network technique performing the best. Other recent work with machine learning models include those that can diagnose or suggest treatment for breast cancer, lung cancer, brain tumors, and even suicide.


This neural network can tell if you're likely to develop Alzheimer's disease in the next three years

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Doctors call this mild cognitive impairment, and it affects most people as they get older. Certain types of PET scans can reveal signs of both these conditions and can therefore be used to spot people with mild cognitive impairment who are most at risk of developing Alzheimer's. This data set consists of brain images of 182 people in their 70s with normal brains and brain images of 139 people of roughly the same age who have been diagnosed with Alzheimer's. Hongyoon and Kyong say their neural network identified those at risk of developing Alzheimer's with an accuracy of 81 percent.