The emergence of artificial intelligence (AI) in the medical field is a result of the increasing demand for customized medical solutions, reduced costs, and increased accuracy of medical decisions and diagnoses to improve patient health outcomes.
and Estimated appraised value With a global market size of $15.1 billion in 2022, AI in healthcare is an irreversible process that is already reshaping medicine, and its projected value will continue to rise in the coming years .
Here are the top 9 innovative ways AI is advancing healthcare.
1. Medical image processing
AI algorithms can analyze complex medical images, from computed tomography (CT) scans to X-rays and magnetic resonance imaging (MRI), helping you:
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An MRI scan is examined to identify brain tumors.
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Analyze CT images to diagnose cerebrovascular diseases and enable timely triage and treatment.
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Recognize early stages of Alzheimer’s disease and dementia by analyzing brain scans and identifying changes in brain structure and volume.
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Detects early stage diabetic retinopathy by scanning retinal images
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Identify diseases such as pneumonia and tuberculosis
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Spotting lung nodules on CT scan
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Analyzing X-rays to detect osteoporosis
AI algorithms provide clinicians with important insights into patient conditions, Speed of diagnosis, accuracy of medical results, and improved health outcomes for patients.
Companies like Ezra use whole body MRI scan Zebra Medical Vision uses AI-driven tools to assist medical professionals with early detection of cancer. X-ray examination shows possible osteoporosis Mammography may indicate breast cancer.
2. surgery
In recent years, robots equipped with AI have become commonplace in operating rooms. These robots can perform tasks that require precision and control;to support surgeons during complex surgeries such as open heart surgery.
The robot is equipped with a mechanical arm, surgical instruments, and a camera. Controlled by the surgeon from a computer console. This gives the surgeon her 3-dimensional magnified view of surgical sites that are difficult or impossible to see, improving the doctor’s skills, knowledge and experience.
The use of AI-powered robots during surgery increases the chances of surgical success, reduces patient complications, shortens post-operative recovery period, and reduces pain.
AI can help surgeons in other ways as well. For example, Theator’s Surgical Intelligence platform analyzes thousands of hours of surgical video and structures data from hundreds of surgeries, allowing surgeons to understand what went well and what didn’t during a surgery. will do so. This research allows surgeons to improve their skills and techniques, save lives and Achieving better health outcomes for patients.
3. Medical research and data analysis
In medical research, scientists use statistical methods to collect and analyze vast amounts of data. This process is often time consuming; ExpensiveAI algorithms can accelerate research by optimizing study design, patient recruitment, and uncovering deeper insights into diseases and treatments.
Additionally, the role of AI extends to analyzing patient records and clinical trial results to establish the effectiveness of new cancer treatments. By employing AI algorithms, researchers can pinpoint specific genetic markers that indicate which patients are most likely to respond positively to treatment. This stratification can minimize the number of patients who do not benefit from a particular treatment, leading to personalized treatment and improving health outcomes for patients in need. Masu.
Building on these advances, Bayer in 2022 investigated how AI algorithms can revolutionize clinical trials. virtual control group To reduce or eliminate the need for “real” control groups in certain clinical trials. In this way, clinical trial control groups select fewer patients for placebo or standard treatment, making drug development more cost-effective and paving the way for smarter, faster, and more patient-centered medical research. will be opened.
Four. drug discovery
Drug development is an expensive and long process, and AI can solve these problems. Machine learning algorithms analyze huge datasets, including genomic data related to diseases, detect potential drug targets, and predict drug efficacy and potential side effects.
The same algorithms can pore over the available scientific literature and support the identification of genetic biomarkers to assess disease, enabling more effective clinical trials and faster time-to-market for therapeutics. I’ll make it.
Additionally, artificial intelligence allows researchers to analyze and repurpose existing drugs to fight specific diseases, making new drug development more cost-effective and effective.. Emerging generative AI is accelerating drug discovery through the design of molecular structures.
Biopharmaceutical company developed by NuMedii Artificial Intelligence for Drug Discovery (AIDD) Technology It “employs deep learning of human biology, consisting of hundreds of millions of structured molecular, pharmacological, and clinical data points that have been carefully selected and harmonized by the company. machine learning and network-based algorithms to discover accurate and effective new drug candidates and biomarkers that predict efficacy for patient subsets across a wide range of therapeutic areas, including rare diseases such as idiopathic diseases. Promoting Pulmonary Fibrosis.
Five. Early detection of deadly blood diseases
AI technology identifies changes in blood cells that are potential indicators of blood disorders. For example, in leukemia, algorithms can analyze a patient’s medical history, blood cell morphology, and genetic data to highlight patterns so subtle that human processing would miss them. This will facilitate the use of AI-driven tools to assist medical professionals by “flagging” the presence of potential signs of leukemia at an early stage.
Additionally, AI can monitor changes that occur in blood cell counts over time and improve the accuracy of detecting disease markers.
For example, Scopio Labs is a developer of full-field cell morphology, an AI-driven imaging platform. Scan and share real-time blood samples in high resolution.
By analyzing thousands of cells in minutes, this app has revolutionized hematology and cell morphology, enabling early detection of hematology-based diseases such as cancer, infections, and anemia. Early detection of these diseases increases patients’ chances of recovery and improves their quality of life.
6. remote patient care
Telepatient care uses AI-powered technology to deliver medical services and monitor patients remotely. Telemedicine is a type of remote patient care that allows patients to receive real-time treatment and consultations no matter where they are. Instead of seeing a doctor in person, you can choose your location. This ensures that even patients in the most remote areas have access to medical services and reduces healthcare costs by reducing hospital visits.
Using AI algorithms, wearable devices worn by diabetics can detect abnormal blood sugar readings and send them to patients and health care professionals. This allows adjustments to treatment plans to be made remotely, helping to control healthcare costs. However, AI can do more than monitor blood sugar levels.
Virtuense, For example, AI is used to remotely identify a patient’s “intention to get out of bed 31 to 65 seconds before getting up” and immediately alert the appropriate staff, helping to reduce the number of falls.
7. Fraud detection
The Centers for Medicare and Medicaid Services (CMS) uses AI and ML toCombat and prevent fraud, waste and abuse”
Fraud is impacting healthcare systems on many levels, and stakeholders have already begun using AI algorithms as tools to combat fraud.
AI processes a wide range of medical and claims data, including insurance companies billed for services not provided, defective test kits and equipment, and surgeons performing unnecessary surgeries to obtain high insurance payouts. helps detect fraud by looking for deviations and irregular patterns. AI can identify and duplicate claims, preventing fraud and ensuring patients benefit from the right care.
AI technology can compare vast amounts of data from multiple sources to determine connections that might be missed by human checks. Additionally, machine learning algorithms adapt over time to improve their ability to identify fraudulent claims. Such developments prevent fraud and result in savings that can be used for their original purpose, such as providing quality care to patients.
8. Accurate early cancer diagnosis
Cancer kills 10 million people every year, leading causes of death around the world. However, if detected and treated early, many cases of cancer can be cured. Given that lung cancer is the number one cause of cancer deaths worldwide, scientists and doctors have designed an AI tool that can accurately detect early lung cancer, speed diagnosis, and direct patients to treatment. Did.
A team of experts from the London Institute of Cancer Research, the Royal Marsden NHS Foundation and Imperial College London used radiomics to identify whether abnormal growths on CT scans are cancerous. Radiomics is a quantitative approach that uses advanced mathematical analysis to enhance the data available to clinicians.In this studyRadiomics was used to extract important information from medical images that are easily missed by the human eye.
The AI model accurately identified large lung cancer nodules, allowing doctors to make faster decisions about intermediate-risk patients with abnormal growth on CT scans. This allows for earlier diagnosis and increases the five-year survival rate compared to if the cancer is detected at a later stage.
9. AI-assisted gene editing in treatment design
Diseases such as sickle cell anemia, cystic fibrosis, and Tay-Sachs disease are caused by misordered DNA letters that codify the operating instructions for every human cell. In some cases, these errors can be corrected with a gene editing process that rearranges these letters.
Other diseases are caused by problems with the way cellular machinery reads DNA, a process known as epigenetics. Traditionally, genes provide the recipe for a particular protein and bind molecules called transcription factors that instruct the cell how much of that particular protein to produce. If this process does not proceed as planned, excess or inactivation of genes can lead to diseases such as cancer, diabetes, and neuropathy. This has led scientists to seek solutions to restore normal epigenetic activity.
Using AI tools, researchers developed zinc finger (ZF) editing, a technology that can change and control genes. According to one researcher, artificial zinc fingers are difficult to design for specific purposes. study The technology, announced in January 2023, could one day help treat diseases caused by multiple genetic factors, from autism to heart disease to obesity.
conclusion
with Globally, it is predicted to reach more than $187 billion by 2030., Artificial intelligence in medicine has become an essential part of our lives and will continue to evolve. To explore its benefits, healthcare organizations and technology companies must work together to ensure that technology is used in a responsible and ethical manner. AI-powered solutions and tools can address many challenges facing health systems, from drug development and remote patient care to early cancer detection and medical imaging. AI can help reduce costs, improve quality of care, and save more lives.
About the author Dr. Liz Kwo is the Chief Commercial Officer of Everly Health, a serial healthcare entrepreneur, physician, and instructor at Harvard Medical School. She received her MD from Harvard Medical School, her MBA from Harvard Business School, and her MPH from Harvard TH Chan School of Public Health. |
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