How can scientists use artificial intelligence to improve the diagnosis and treatment of a variety of human diseases?

-Hypertension: Scientists hope to use artificial intelligence technology to screen people at high risk of cardiovascular disease doi:10.1161/hyp.76.suppl_1.MP10 Now there is growing research evidence that bacteria living in the body's digestive tract can have far-reaching effects on the body's cardiovascular health. In a recent study published in the international journal Hypertension, scientists from institutions such as the University of Torredo say that today we may not need specialized testing, but use these microbes to help diagnose heart and vascular disease. 'We are well aware of the link between an individual's gut microbiome and a variety of diseases, such as high blood pressure and heart failure, although we are not entirely aware of all the mechanisms involved, and using artificial intelligence, researchers can develop a new machine learning model that simply uses bacterial properties in feces to screen people for cardiovascular disease,' said
researcher Bina Joe. in the
article, the researchers used computer algorithms to analyze the bacterial composition of stool samples from about 1,000 individuals, about half of whom were diagnosed with some form of cardiovascular disease, while the other half reported no cardiovascular disease.
picture source: CC0 Public Domain 6 Nature Interpretation! How new artificial intelligence technology unlocks the mysteries of changes in virus control cells! Doi:10.1038/s41586-020-2714-x Scientists from Northwestern University and others have developed a new AI technology (artificial intelligence technology) that could help identify changes in the cells of viruses, according to a study published in the international journal Nature entitled "Cytoplasmic control of intranuclear polarity by human cytomegairlovus."
researchers point out that viruses control structure and genetic polarity in the nucleus, a finding that underscores the importance of genomic tissue during infection and the extent to which AI technology can help scientists identify complex intracellular changes.
Viruses can control cells in a variety of ways, from viral proteins that are present in the nucleus that directly control gene expression to proteins that can play a role in controlling cellular signaling networks on cell surfaces or cytones, and the researchers say how and why the nucleus moves and recombines in a variety of situations, including during viral infections, may be a question that needs to be studied in depth at a later stage.
A central question in studying any intracellular process is how heterogeneic the events that occur in each single cell in the cell culture, and we can have some un-infected cells during the infection process, some of which fail, and in those infected cells, each cell is at a different stage of infection, which may be difficult to control or synchronize experimentally.
Rev Neurol: Artificial intelligence technology may accelerate and improve the diagnosis of Alzheimer's disease doi:10.1038/s41582-020-0377-8 Recently, a study appeared in the international journal Nature Reviews Neurology In the study, scientists from institutions such as the University of Sheffield said the use of artificial intelligence (AI) could help rapidly diagnose Alzheimer's disease and improve the prognosis of patients; in the paper, researchers analysed how AI could be used in the medical field to help improve the time and economic impact of common neurodegenerative diseases on the NHS, such as Alzheimer's and Parkinson's disease.
The main risk factor for many neurological disorders is age, and as life expectancy increases globally, the number of people with neurodegenerative diseases is expected to reach an unprecedented number, with researchers predicting that the number of Alzheimer's patients alone will triple by 2050. Reaching 115 million, this poses a challenge to health systems; in this study, researchers used AI techniques, such as machine learning algorithms, to detect neurodegenerative diseases before symptoms worsened, improving patients' chances of benefiting from successful disease modification therapies.
: New algorithms may use artificial intelligence to help manage doi:10.1038/s42255-020-0212-y In a recent study published in the international journal Nature Metabolism, scientists from institutions such as Oregon Health and Science University used artificial intelligence and automated monitoring to develop a new method that could help people with type 1 diabetes better manage their blood sugar levels.
researcher Dr Nicole Tyler said: 'Our system design is unique, and in this article we used a special mathematical simulator to design artificial intelligence algorithms, but when they were validated on real data from people with type 1 diabetes, the recommendations were highly similar.
this is important because it often takes 3-6 months for diabetics to make appointments and visits with endocrinologists.
During this time, patients with type 1 diabetes are unable to produce enough insulin themselves to control their blood sugar if their blood sugar levels are too high or too low, so they must control blood sugar by using insulin pumps or multiple insulin injections a day, a new algorithm developed by researchers that uses data collected from continuous glucose monitoring devices and wireless insulin pens to guide patients' treatment.
when used with a mobile app called DailyDose, the algorithm's recommendations showed that it was in line with the doctor's opinion 67.9 percent of the time.
: Diagnosing Breast Cancer Artificial Intelligence Wins Over Human Experts! doi:10.1038/s41586-019-019 In a recent study published in the international journal Nature, scientists from Google Health developed a new type of computer program that can diagnose and detect breast cancer with greater accuracy than human experts through routine scans.
Breast cancer is the most common type of cancer in the female population, with more than 2 million newly diagnosed cases last year alone, and regular screening is essential to detect early symptoms of the disease in the group of patients with no obvious symptoms;
But there is often room for error in the interpretation of scan results, and a small percentage of all mammoth X-rays show false positives (misdiagnosing healthy people as having cancer) or false negatives (misdiagnosing disease positives as negative).
In this study, researchers used artificial intelligence models to scan thousands of women in the UK and the US for breast cancer; these images have been analysed and examined by doctors in real life, but unlike clinical environments, machines (artificial intelligence algorithms) do not diagnose diseases based on a patient's medical history.
10) Nature Sub-Journal: Artificial Intelligence Power Leukemia Diagnosis Doi:10.1038/s42256-019-0101-9 Daily, Medical