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If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Minh-Hoang Tran,1 Ngoc Quy Nguyen,2 Hong Tham Pham1,3 1Department of Pharmacy, Nhan Dan Gia Dinh Hospital, Ho Chi Minh City, Vietnam; 2Institute of Environmental Technology and Sustainable Development, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam; 3Department of Pharmacy, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam Correspondence: Hong Tham Pham, Department of Pharmacy, Nguyen Tat Thanh University, Ho Chi Minh City, Vietnam, Tel 84 919 559 085, Email [email protected] Abstract: Recent years have witnessed the rise of artificial intelligence (AI) in antimicrobial resistance (AMR) management, implying a positive signal in the fight against antibiotic-resistant microbes. The impact of AI starts with data collection and preparation for deploying AI-driven systems, which can lay the foundation for some effective infection control strategies. Primary applications of AI include identifying potential antimicrobial molecules, rapidly testing antimicrobial susceptibility, and optimizing antibiotic combinations. Aside from their outstanding effectiveness, these applications also express high potential in narrowing the burden gap of AMR among different settings around the world. Despite these benefits, the interpretability of AI-based systems or models remains vague.
With recent advances in communication networks and machine learning (ML), healthcare is one of the key application domains which stands to benefit from many opportunities, including remote global healthcare, hospital services on cloud, remote diagnosis or surgeries, among others. One of those advances is network slicing, making it possible to provide high-bandwidth, low-latency and personalized healthcare services for individual users. This is important for patients using healthcare monitoring devices that capture various biological signals (biosignals) such as from the heart (ECG), muscles (EMG), brain (EEG), or activities from other parts of the body. In this blog, we discuss the challenges to building a scalable delivery platform for such connected healthcare services, and how technological advances can help to transform this landscape significantly for the benefit of both users and healthcare service providers. Our specific focus is on assistive technology devices which are increasingly being used by many individuals.
In this interview, we talk to Takayuki Baba from Fujitsu Research about ongoing research using artificial intelligence to achieve earlier diagnosis of pancreatic cancer. I am Takayuki Baba, and I am researching medical image diagnosis support technology as a "converging technology" that combines image analysis technology and medical science at Fujitsu Research. Converging technologies combine two or more different social sciences and technology areas to achieve a specific goal and represent a major focus of Fujitsu's R & D. Fujitsu Research has a track record in the research and development of technologies for the detection of multiple types of lesions on computed tomography (CT) images with AI and the retrieval of past CT images with a similar distribution of lesions, which are used in medical diagnostic imaging support technologies to help physicians make diagnoses. Fujitsu and the Southern Tohoku General Hospital have started joint research with Fujitsu Japan Limited and FCOM CORPORATION on AI technology for detecting pancreatic cancer from non-contrast CT images through FCOM, which has been supporting the medical system of Southern Tohoku General Hospital. The survival rate for pancreatic cancer is said to be low, as it is often found when it has already progressed to a state that is difficult to treat.
Facebook parent company Meta said it's created a new AI platform that builds realistic simulations of the muscles, bones and joints that enable humans to move. Studying the human body's musculoskeletal system could help Meta create more-realistic avatars in virtual worlds. The social media giant is challenging researchers to improve these models. Facebook parent company Meta said Monday that it's created a new artificial intelligence platform that could help the social media giant develop more-realistic avatars for virtual worlds. Today, avatars that exist in digital spaces look like cartoons and don't move as fluidly as humans do in real life. Meta thinks the key to improving these avatars could be in learning more about the bones, muscles and joints that make up the human body's musculoskeletal system.
BackgroundHandwriting is an acquired complex cognitive and motor skill resulting from the activation of a widespread brain network. Handwriting therefore may provide biologically relevant information on health status. Also, handwriting can be collected easily in an ecological scenario, through safe, cheap, and largely available tools. Hence, objective handwriting analysis through artificial intelligence would represent an innovative strategy for telemedicine purposes in healthy subjects and people affected by neurological disorders.Materials and MethodsOne-hundred and fifty-six healthy subjects (61 males; 49.6 ± 20.4 years) were enrolled and divided according to age into three subgroups: Younger adults (YA), middle-aged adults (MA), and older adults (OA). Participants performed an ecological handwriting task that was digitalized through smartphones. Data underwent the DBNet algorithm for measuring and comparing the average stroke sizes in the three groups. A convolutional neural network (CNN) was also used to classify handwriting samples. Lastly, receiver operating characteristic (ROC) curves and sensitivity, specificity, positive, negative predictive values (PPV, NPV), accuracy and area under the curve (AUC) were calculated to report the performance of the algorithm.ResultsStroke sizes were significantly smaller in OA than in MA and YA. The CNN classifier objectively discriminated YA vs. OA (sensitivity = 82%, specificity = 80%, PPV = 78%, NPV = 79%, accuracy = 77%, and A...
Just a half-millimeter wide, the tiny crabs can bend, twist, crawl, walk, turn and even jump. The researchers also developed millimeter-sized robots resembling inchworms, crickets and beetles. Although the research is exploratory at this point, the researchers believe their technology might bring the field closer to realizing micro-sized robots that can perform practical tasks inside tightly confined spaces. The research will be published on Wednesday (May 25) in the journal Science Robotics. Last September, the same team introduced a winged microchip that was the smallest-ever human-made flying structure.
The objective of this study is to classify medical images using the Convolutional Neural Network(CNN) Model. Here, I trained a CNN model with a well-processed dataset of medical images. This model can be used to classify medical images based on categories provided as per the training dataset. This dataset was developed in 2017 by Arturo Polanco Lozano. It is also known as the MedNIST dataset for radiology and medical imaging. For the preparation of this dataset, images have been gathered from several datasets, namely, TCIA, the RSNA Bone Age Challange, and the NIH Chest X-ray dataset.
An adorable robotic crab has been developed by scientists – but you'll need a magnifying glass if you want to see it. The tiny bot is inspired by peekytoe crabs and measures just 0.02 inches (0.5mm) wide, making it the smallest ever remote-controlled walking robot. Despite being smaller than a flea, the robot can bend, twist, crawl, walk, turn, and even jump. Researchers from Northwestern University, who developed the robot, believe the bot could be used to perform a range of tasks in confined spaces. 'You might imagine micro-robots as agents to repair or assemble small structures or machines in industry or as surgical assistants to clear clogged arteries, to stop internal bleeding or to eliminate cancerous tumours -- all in minimally invasive procedures,' said Professor John Rogers, who led the project.
A new artificial intelligence sleep app has been developed that might be able to replace sleeping pills for insomnia sufferers. Sleepio uses an AI algorithm to provide individuals with tailored cognitive behavioural therapy for insomnia (CBT-I). The National Institute for Health and Care Excellence (Nice) said it would save the NHS money as well as reduce prescriptions of medicines such as zolpidem and zopiclone, which can be dependency forming. Its economic analysis found healthcare costs were lower after one year of using Sleepio, mostly because of fewer GP appointments and sleeping pills prescribed. The app provides a digital six-week self-help programme involving a sleep test, weekly interactive CBT-I sessions and keeping a diary about sleeping patterns.
Human beings, as we know, really boast a wide range of skills, but if we have to pick the most valuable one from the lot, it's going to be our problem-solving capabilities. You see, this particular skill is really what allows us to answer different questions in life, and consequentially, take that next step in our journey. Now, even though the stated element has proved to be helpful pretty much by default, we have still tried to enhance it over the years. Talk about how we did it, we would actually end up inculcating a unique set of ideas. However, in hindsight, it's hard to put any of those ideas above a certain one called technology.