The NHS has introduced a revolutionary new app to help diagnose Alzheimer's Disease. It takes only five minutes to complete and is more accurate than established pen-and-paper tests. The test is currently done on iPads at a general practice or hospital ward but it could soon be conducted at home on a smart phone – paving the way for the nation's first widespread screening programme for Alzheimer's and other forms of dementia within the next few years. It is hoped it will identify people at high-risk of developing the disease up to 15 years before symptoms appear, so that steps can be taken to slow its progression. The test uses artificial intelligence to assess a person's brain function by showing them large numbers of black and white photographs and asking them to identify which ones contain an animal.
Powerful algorithms used by Netflix, Amazon and Facebook can'predict' the biological language of cancer and neurodegenerative diseases like Alzheimer's, scientists have found. Big data produced during decades of research was fed into a computer language model to see if artificial intelligence can make more advanced discoveries than humans. Academics based at St John's College, University of Cambridge, found the machine-learning technology could decipher the'biological language' of cancer, Alzheimer's, and other neurodegenerative diseases. Their ground-breaking study has been published in the scientific journal PNAS today (April 8 2021) and could be used in the future to'correct the grammatical mistakes inside cells that cause disease'. Professor Tuomas Knowles, lead author of the paper and a Fellow at St John's College, said: "Bringing machine-learning technology into research into neurodegenerative diseases and cancer is an absolute game-changer. Ultimately, the aim will be to use artificial intelligence to develop targeted drugs to dramatically ease symptoms or to prevent dementia happening at all."
Developed by experts from Sweden's Lund University, the approach has the potential to speed up diagnoses while removing the need for costly, specialist equipment. At present, some 20–30 per cent of patients with Alzheimer's disease are misdiagnosed in specialist care alone, let alone primary care, the team noted. A new tool -- using just a blood test (pictured) and a quick set of cognitive tests -- can predict whether someone will develop Alzheimer's in four years with 90 per cent accuracy'Our algorithm is based on a blood analysis of phosphylated rope and a risk gene for Alzheimer's, as well as testing of memory and executive ability,' said neurologist Sebastian Palmqvist of Lund University and the Skåne University Hospital. 'We have developed an online tool to calculate the risk at the individual level that a person with mild memory difficulties will develop Alzheimer's within four years.' In their study, Professor Palmqvist and colleagues examined 340 people with mild memory difficulties who had been recruited into the Swedish BioFINDER Study into neurodegenerative diseases and 543 people from North America.
Beijing, May 26 (Reporter Zhang Su) at a seminar held in the "cloud", Chinese and Russian scientists focused on the application scenarios of artificial intelligence in the field of brain science, Alzheimer's disease imaging technology, the path and future development of artificial intelligence technology in neurobiology are discussed. The reporter learned from the Beijing Science and Technology Association on the 26th that at the cross-academic seminar on Sino-Russian brain science and artificial intelligence, from Moscow Lomonosov National University (MSU), Russian Academy of Sciences (RAS) and Beijing Neuroscience Society, experts and scholars from the Beijing Brain Science and Brain-like Research Center exchanged views on the latest scientific research progress and cross-evolving new situation in the field of brain science and artificial intelligence between China and Russia. At the seminar, Executive Director, Brain Intelligence Research Center, Beijing Brain Science and Brain-like Research Center, yang Yuchao, director of the Brain-like Intelligent Chip Research Center of the Institute of Artificial Intelligence, Peking University, made a report entitled "Brain-inspired Hardware Prototype for Efficient Computing Applications"; Chief researcher of the Institute of Mathematics, Russian Academy of Sciences, ivan oseeldets, director of the Intelligent Computing Laboratory of Skolkovo Institute of science and technology, made a report entitled "realistic challenges of artificial intelligence technology; liu Yong, a professor at the School of Artificial Intelligence, Beijing University of Posts and Telecommunications, gave a report entitled" The Application of Artificial Intelligence Technology in the Research of Biomarkers of Alzheimer's Disease "; Director of the Institute of Advanced Brain Science, Moscow University, konstantin Anokhin, academician of the Russian Academy of Sciences, gave a report entitled" The missing link of neural and artificial intelligence. Beijing Association for Science and Technology, vice chairman of the China Association for Science and Technology Life Commonwealth, vice chairman of the Chinese Nutrition Society chairman yang yue xin, vice-president, took the chair. She said that the Beijing Association for Science and Technology closely revolves around the construction of the capital's international science and technology innovation center and the International Exchange Center, fully unblocked and used the channels of non-governmental scientific and technological exchanges, and closely integrated the academic pursuit of scientific and technological workers with the needs of the capital's innovation and development, invite scientists and foreign colleagues to conduct in-depth exchanges and discussions on cutting-edge scientific issues and international project cooperation, and support scientific and technological workers in the capital to make a "capital academic" voice on the international stage.
An artificial intelligence-based analysis of epigenetic patterns in blood samples might be able to identify people with Alzheimer's disease, a new study has found. Alzheimer's disease affects nearly 47 million people around the world but can be difficult to diagnose, particularly in its early stages when therapeutic interventions might have the greatest effect. "Drugs used in the late stage of the disease do not seem make much difference, so there is a tremendous amount of interest in diagnosis in the early stages of the disease," Khaled Imam, director of geriatric medicine at Beaumont Health and a co-author of the new study, said in a statement. Imam added that "blood is thought to be a desirable way of approaching this. And it would be relatively cheap and minimally invasive as compared to an MRI or spinal tap."
The world's first Alzheimer's disease (AD) drug candidate designed by artificial intelligence (AI) is entering Phase I clinical trials, thanks to a successful collaboration between Exscientia Ltd and Sumitomo Dainippon Pharma. In the announcement from Exscientia, it states that they will initiate a Phase 1 clinical study of DSP-0038 in the United States for the treatment of Alzheimer's disease psychosis. DSP-0038 is the third molecule created using Exscientia's Artificial Intelligence (AI) technologies to enter clinical trials. The two earlier compounds are DSP-1181, announced in 2020 together with Sumitomo Dainippon Pharma to treat obsessive-compulsive disorder, and Exscientia's immuno-oncology agent, EXS-21546, announced earlier this year. Joint research between Exscientia and Sumitomo Dainippon Pharma designed DSP-0038 to be a single small molecule that exhibits high potency as an antagonist for the 5-HT2A receptor and agonist for the 5-HT1A receptor, whilst selectively avoiding similar receptors and unwanted targets, such as the dopamine D2 receptor.
AI has been at the forefront of the medical profession's efforts to fight Covid-19 and treat patients during the coronavirus pandemic. Enabling healthcare providers to make fast, accurate and data-driven decisions, the technology has been producing some extraordinary outcomes. Outside the Covid crisis, machine intelligence is lending itself to hundreds of medical applications, from scanning vast numbers of people to assess their risk of dementia to accelerating the drug discovery process. Here is just a small selection of cases where the technology is revolutionising healthcare provision. Healthcare professionals are using AI-powered speech-recognition systems to update electronic patient records more quickly and accurately.
Paul De Sousa, head of life sciences at Massive Analytic and former researcher at Edinburgh University, writes about a study using artificial precognition AI to analyse results of protein biomarker tests associated with Alzheimer's disease progression. Accounting for over 30 million Disability Adjusted Life Years worldwide, Alzheimer's disease (AD) is a global societal challenge and a threat to healthcare systems around the world. A long history of failures of AD drug trials has highlighted the need for early detection and diagnosis to support patients and clinicians to implement the best life adjustments or medical interventions to alter the course of the disease and personalise the care of those at risk. Biomarkers are measurable indicators of the biological conditions of health, on which disease prognosis and diagnosis is founded. In AD there are a range of diagnostic procedures to detect these biomarkers including testing Cerebrospinal fluid (CSF) and PET scans for markers of amyloid-β and tau that can accurately detect AD pathology, but their cost and invasive nature preclude the broad accessibility required for early detection.
When it comes to neurodegenerative diseases, Alzheimer's disease is considered one of the worst. It promotes the onset of dementia--an irreversible decline in thinking, memory, and ability to perform simple everyday tasks--in around 60 to 70 percent of patients. Now, researchers have suggested that the disease can be divided into four distinct subtypes; potentially opening doors for individualized treatment among sufferers. In an international study, scientists illustrated that tau--proteins found in neurons that are associated with neurodegenerative conditions--spread through the brain in four distinct patterns. This leads to varied symptoms and outcomes among affected individuals. Machine learning (ML) was leveraged by the authors to distinguish between the different subtypes.