alzheimer s disease


Five damaging myths about video games – let's shoot 'em up

The Guardian

Video games are one of the most misunderstood forms of entertainment. In one sense, it's easy to see why: if you haven't had much interaction with them, watching someone play one can be a pretty unsettling experience. Gamers can often give the impression that they're glued to the screen, absorbed in what feels like the digital equivalent of junk food. At best, it seems like a pointless thing to do; at worst, we worry that games are socially isolating, or actively harmful. One of the longest-standing tropes about video games is that violent ones – like Call of Duty or Fortnite – can cause players to become more aggressive in the real world.


3D-printed transparent mouse skull could be window to studying Alzheimer's and head injuries

Daily Mail

A transparent mouse skull which can be used as a window to the brain could provide new insights into human brain conditions like Alzheimer's disease. Researchers have developed the implant as an'unprecedented' way to monitor and visualise brain activity. Named the See-Shell, it's a 3D-printed replica of the animal's skull which can be used to surgically replace part of the mouse's head. Once in place, the See-Shell allows researchers to both record brain activity and take photos or video of the brain's surface in real time. The See-Shell allows scientists to see mice's brains in real time and picture changes in electrical activity as different areas of the organ are stimulated Scientists at the University of Minnesota developed the implant as a way of getting a better insight into the live brain's workings.


AI Is Good (Perhaps Too Good) at Predicting Who Will Die Prematurely

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Medical researchers have unlocked an unsettling ability in artificial intelligence (AI): predicting a person's early death. Scientists recently trained an AI system to evaluate a decade of general health data submitted by more than half a million people in the United Kingdom. Then, they tasked the AI with predicting if individuals were at risk of dying prematurely -- in other words, sooner than the average life expectancy -- from chronic disease, they reported in a new study. The predictions of early death that were made by AI algorithms were "significantly more accurate" than predictions delivered by a model that did not use machine learning, lead study author Dr. Stephen Weng, an assistant professor of epidemiology and data science at the University of Nottingham (UN) in the U.K., said in a statement. To evaluate the likelihood of subjects' premature mortality, the researchers tested two types of AI: "deep learning," in which layered information-processing networks help a computer to learn from examples; and "random forest," a simpler type of AI that combines multiple, tree-like models to consider possible outcomes.


Alana gift to MIT launches Down syndrome research center, technology program for disabilities

MIT News

As part of its continued mission to help build a better world, MIT is establishing the Alana Down Syndrome Center, an innovative new research endeavor, technology development initiative, and fellowship program launched with a $28.6 million gift from Alana Foundation, a nonprofit organization started by Ana Lucia Villela of São Paulo, Brazil. In addition to multidisciplinary research across neuroscience, biology, engineering, and computer science labs, the gift will fund a four-year program with MIT's Deshpande Center for Technological Innovation called "Technology to Improve Ability," in which creative minds around the Institute will be encouraged and supported in designing and developing technologies that can improve life for people with different intellectual abilities or other challenges. The Alana Down Syndrome Center, based out of MIT's Picower Institute for Learning and Memory, will engage the expertise of scientists and engineers in a research effort to increase understanding of the biology and neuroscience of Down syndrome. The center will also provide new training and educational opportunities for early career scientists and students to become involved in Down syndrome research. Together, the center and technology program will work to accelerate the generation, development, and clinical testing of novel interventions and technologies to improve the quality of life for people with Down syndrome.


Dilated deeply supervised networks for hippocampus segmentation in MRI

arXiv.org Artificial Intelligence

Tissue loss in the hippocampi has been heavily correlated with the progression of Alzheimer's Disease (AD). The shape and structure of the hippocampus are important factors in terms of early AD diagnosis and prognosis by clinicians. However, manual segmentation of such subcortical structures in MR studies is a challenging and subjective task. In this paper, we investigate variants of the well known 3D U-Net, a type of convolution neural network (CNN) for semantic segmentation tasks. We propose an alternative form of the 3D U-Net, which uses dilated convolutions and deep supervision to incorporate multi-scale information into the model. The proposed method is evaluated on the task of hippocampus head and body segmentation in an MRI dataset, provided as part of the MICCAI 2018 segmentation decathlon challenge. The experimental results show that our approach outperforms other conventional methods in terms of different segmentation accuracy metrics.


iTWire - IBM Research finds way to detect Alzheimer's Disease early via ML-based blood test

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Alzheimer's disease is a terminal neurodegenerative disease that has historically been diagnosed based on observing significant memory loss. There is currently no cure or disease-modifying therapy for this terminal illness, despite hundreds of clinical trials. It is thought these trials may have a high failure rate because the people enrolled are in the latest stages of the disease, likely already suffering a level of brain tissue loss that cannot easily be repaired. Thus, researchers have put their mind to how to detect this disease earlier, while a chance may still exist to slow its progression. Recent research has shown a biological marker associated with the disease, a peptide called amyloid-beta, changes decades before any memory-related issues are apparent.


How Artificial Intelligence Could Transform Medicine

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Last month, President Trump signed an executive order making the development and regulation of artificial intelligence a federal priority. But one area where artificial intelligence is already taking hold is health care. Doctors are already using A.I. to spot potentially lethal lesions on mammograms. Scientists are also developing A.I. systems that can diagnose common childhood conditions, predict whether a person will develop Alzheimer's disease and monitor people with conditions like multiple sclerosis and Parkinson's disease. Dr. Eric Topol, a cardiologist and the founder and director of the Scripps Research Translational Institute, has long heralded this convergence of technology and medicine.


IBM takes on Alzheimer's disease with machine learning

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IBM has introduced machine learning (ML) to the diagnostics field in the hopes that one day these technologies may assist in the creation of stable and effective diagnostic tests for early-onset Alzheimer's. On Monday, the tech giant said ML and artificial intelligence (AI) can be exploited to replace invasive and expensive tests for the disease. A paper documenting the research, conducted by IBM's Australian team, has been published in Scientific Reports. Alzheimer's is currently incurable and can only be treated by palliative means. Symptoms for the disease include the gradual degradation of memory, confusion, and difficulty in completing once-familiar daily tasks.


IBM takes on Alzheimer's disease with machine learning

ZDNet

IBM has introduced machine learning (ML) to the diagnostics field in the hopes that one day these technologies may assist in the creation of stable and effective diagnostic tests for early-onset Alzheimer's. On Monday, the tech giant said ML and artificial intelligence (AI) can be exploited to replace invasive and expensive tests for the disease. A paper documenting the research, conducted by IBM's Australian team, has been published in Scientific Reports. Alzheimer's is currently incurable and can only be treated by palliative means. Symptoms for the disease include the gradual degradation of memory, confusion, and difficulty in completing once-familiar daily tasks.


IBM's AI blood test could help with early Alzheimer's detection

Engadget

Previous attempts to find a cure for Alzheimer's ended up in failure, but a new study out of IBM Research has the potential to spark a major breakthrough. A group of IBM researchers have harnessed the powers of machine learning to figure out a way to detect a biological marker associated with the disease -- a peptide called amyloid-beta -- with a simple blood test. The solution they came up with can even detect an individual's risk for Alzheimer's earlier than a brain scan can and way before symptoms start showing up. It can arm doctors with the ammo they need to be able to take better care of their patients. According to a study published in 2017, the concentration of amyloid-beta in a person's spinal fluid starts changing decades before the first signs of the disease show up.