Collaborating Authors

Alzheimer's Disease

Magnetic microbots can hook up brain cells to make a neural network

New Scientist

Tiny robots that can transport individual neurons and connect them to form active neural circuits could help us study brain disorders such as Alzheimer's disease. The robots, which were developed by Hongsoo Choi at the Daegu Gyeongbuk Institute of Science and Technology in South Korea and his colleagues, are 300 micrometres long and 95 micrometre wide. They are made from a polymer coated with nickel and titanium and their movement can be controlled with external magnetic fields.

Fran Allen

Communications of the ACM

Frances E. Allen, an American computer scientist, ACM Fellow, and the first female recipient of the ACM A.M. Turing Award (2006), passed away on Aug. 4, 2020--her 88th birthday--from complications of Alzheimer's disease. Allen was raised on a dairy farm in Peru, NY, without running water or electricity. She received a BS degree in mathematics from the New York State College for Teachers (now the State University of New York at Albany). Inspired by a beloved math teacher, and by the example of her mother, who had also been a grade-school teacher, Allen started teaching high school math. She needed a master's degree to be certified, so she enrolled in a mathematics master's program at the University of Michigan.

Artificial intelligence diagnoses Alzheimer's with more than 95% accuracy


An artificial intelligence (AI) algorithm has produced another significant breakthrough using attention mechanisms and a convolutional neural network to accurately identify tell-tale signs of Alzheimer's. The AI tool developed by the Stevens Institute of Technology is said to be able to explain its conclusions, thus enabling human experts to check the accuracy of its diagnosis by up to 95%. AI has made huge strides in the medical sector and this latest news is further evidence that the speed at which the technology is moving shows no signs of ceasing any time soon. The algorithm is trained to identify subtle linguistic patterns previously overlooked by using texts composed by both healthy subjects and known Alzheimer's sufferers. The team of researchers then converted each sentence into a unique numerical sequence, or vector, representing a specific point in a 512-dimensional space.

AI diagnoses Alzheimer's with more than 95% accuracy


An artificial intelligence (AI) algorithm has produced another significant breakthrough using attention mechanisms and a convolutional neural network to …

Bid to use AI to help diagnose Parkinson's and Alzheimer's with eye scans


Neurological conditions such as Parkinson's and Alzheimer's could be diagnosed from simple eye scans performed by high street opticians thanks to a new NHS artificial intelligence (AI) project. Newcastle University is working on the project with medics at North East hospitals as part of a national £50 million boost to use AI in a range of health schemes. Early diagnosis in progressive neurological diseases such as Parkinson's and Alzheimer's, which affect more than one million people in the UK, is important, so speeding up the process could be crucial. Anya Hurlbert, professor of visual neuroscience at Newcastle University, is leading the Octahedron project. She said: "The retina at the back of the eye is basically an outpost of the brain and the only part of the central nervous system we can see directly from the outside. "We know that in Alzheimer's disease and Parkinson's disease the retina is affected." Very detailed images of the retina can be captured by optical coherence tomography, or OCT scanning, which is quick and cheap and increasingly available at high street opticians. Further analysis of these scans will now be developed with the use of AI, to recognise signs of neurological disease. Prof Hurlbert said: "The aim of the project is to use NHS data to teach computers how to detect early signs of neurological disease via retinal imaging.

Scientists create AI tool that detects Alzheimer's through speech


Detecting Alzheimer's in its early stages remains quite the mystery for scientists. In an effort to solve this mystery, a team of researchers are utilizing artificial intelligence to look for signs of Alzheimer's within language.

AI algorithm detects signs of Alzheimer's disease through language


With no cure and no straightforward way of diagnosing the disease, scientists are exploring every avenue when it comes to detecting Alzheimer's during its early stages. One group of researchers has turned its attention to subtle differences in the language of sufferers, and have developed an AI tool they say can pick up on these as a way of potentially screening for the disease. The research was carried out at New Jersey's Stevens Institute of Technology and focuses on the way some Alzheimer's sufferers express themselves. The disease, and others that cause dementia, can impact some parts of the brain that control language, meaning that sufferers can struggle to find the right words, perhaps using the word "book" to describe a newspaper, or replacing nouns with pronouns, for example. "Language deficits occur in eight to 10 percent of individuals in the early stages of Alzheimer's disease (AD), and become more severe and numerous during its later stages," lead author of the study, K.P. Subbalakshmi explains to New Atlas.

IBM announces AI based chemistry lab: RoboRXN


IBM has announced on its blog page the development of an AI/cloud-based chemistry lab named RoboRXN. Its purpose is to help chemists develop new materials in a faster and more efficient way than the current trial-and-error process. For thousands of years, humans have devised new materials by combining other raw materials, quite often through the use of treatments to instigate chemical reactions. However, the trial-and-error method--an oftentimes tedious and expensive endeavor--has remained relatively unchanged over the years. As part of its announcement, IBM suggests that in the modern age, it costs on average $10 million (and takes on average 10 years) for a company to develop a useful new material.

Aussie researchers leverage compute power to analyse genomic data and match donors


The Commonwealth Scientific and Industrial Research Organisation (CSIRO) has announced a team of researchers have processed one trillion points of genomic data in its fight to pinpoint the location of specific disease-causing genes in the human genome. Using VariantSpark, CSIRO's artificial intelligence-based library for genomic data analysis, the researchers are looking for a deeper understanding of complex diseases by analysing large genomic datasets. "Our VariantSpark platform can analyse traits, such as diseases or susceptibilities, and uncover which genes may jointly cause them," CSIRO Bioinformatics Group leader Dr Denis Bauer said. "This can provide valuable information about how the disease works on a molecular level, which can ultimately lead to better treatments." She said VariantSpark is being used to help determine what genes might be linked to cardiovascular disease, motor neurone disease, dementia, and Alzheimer's disease.

Modern Science: Artificial Intelligence can Help Diagnose Your Health Conditions via Selfies - Health Writeups


The advancement in science and medicine has helped save millions of lives up till now. The artificial intelligence is a modern technique of diagnosing pathologies with more accuracy than ever before. On 21th August, a study in the European Heart Journal published a methodology to diagnose heart disease. It suggests people pass on selfies to their respective doctors for analyzing their heart disease stage, if there is any, by using deep learning. The new deep learning has taken one-step forward in diagnosing Alzheimer's disease in its early stage.