artificial intelligence or AI is taking the World by storm and its impact will be felt in all corners of society including medicine here are four ways AI is transforming the medical field Dodger Jubal Med schoolinsiders.com the first way AI is changing medicine is by assisting with diagnosing and treating patients misdiagnosing a disease happens relatively infrequently but it can occur due to factors
such as physician fatigue errors in diagnostic modalities or limited resources in underprivileged areas while the idea of AI taking over disease diagnosis may sound alarming we should view it as a supportive tool for Physicians for example the convolutional neural network or CNN is a diagnostic modality that can analyze thousands of images from public data sets and patient medical records to identify
patterns enabling them to quickly and accurately diagnose diseases researchers recently used cnns to diagnose Kawasaki disease or KD an inflammatory disease of the blood vessels in children that can prove fatal if left untreated a diagnostic hurdle with KD is that symptoms are usually vague and can
overlap with other childhood illnesses to reduce the rate of misdiagnosis researchers compiled images from KD patients from all over the world building a CNN that can identify its common signs the CNN proved both sensitive and specific for diagnosing Kawasaki disease making diagnosis possible by merely taking a photo with a smartphone of course clinical judgment currently remains Irreplaceable and
How AI Improves Patient Diagnosis
Physicians should still rely on a thorough history physical exam and the relevant Labs or Imaging these cnns can help guide physicians in the right direction especially in resource restricted locales where it can
be expensive for patients to do more thorough testing preliminary efforts have also demonstrated AI can Aid clinicians in diagnosing colorectal cancer lung cancer liver cirrhosis and many more diseases in one study board-certified Pathologists diagnosed colorectal cancer with 96.9 accuracy and AI
slightly outperformed them reaching an accurate diagnosis 98 of the time however doctors shouldn’t forget about the limitations of AI in diagnosing disease biases can exist in any of the data sets which can influence the way AI interprets the diagnosis for example if a data set is mostly made up of older patients AI might not be able to accurately interpret findings for a younger age group after diagnosis AI
can also Aid physicians in treatment particularly in the era of personalized medicine personalized medicine is a form of medicine that uses information about a person’s genetics to prevent diagnose or treat disease one specific example of this is rheumatoid arthritis and autoimmune disease where the body attacks itself especially in joints like the wrist and finger joints since rheumatoid arthritis is such a
AI in Medical Imaging and Analysis
complex and chronic disease there are a variety of medications used to treat patients and treatment often depends on what each patient best responds to researchers at Mayo Clinic use genetic data and patients clinical characteristics to develop a machine learning algorithm to predict patient response to Methotrexate one of the most important arthritis drugs instead of having both doctors and patients wait
months to determine the efficacy of a certain drug these models can direct both doctors and patients toward more effective treatments immediately saving the patient both time and money similarly researchers at the Georgia Institute of Technology and ovarian cancer institute utilized machine learning
algorithms to determine treatment Effectiveness with 90 accuracy for certain chemotherapies in ovarian cancer patients utilizing AI to predict a patient’s response to chemotherapy can save valuable time and spare patients from the destructive physical side effects emotional burden and costs associated with weeks of treatment that may prove ineffective Beyond diagnosis and treatment AI has powerful
potential in predicting the occurrence and progression of chronic diseases like hypertension diabetes and kidney disease which can help patients live longer healthier lives let’s take a closer look at diabetes using various machine learning models researchers are developing predictive models to estimate a patient’s current glucose level based on multiple factors such as their previous glucose levels body mass
Personalized Treatment Plans with AI
index external stress and even hours of sleep this can help patients anticipate when their blood sugar levels are critically high or low enabling them to better prepare for emergencies researchers have also used AI to develop models that predict the likelihood of developing diabetes based on various risk factors early diagnosis and treatment of diabetes can prevent complications like diabetic kidney disease
and blindness which are emotionally distressing and costly for both patients and the Health Care system in addition to Patient Care AI is also furthering Medicine by transforming the way medical research is conducted particularly in clinical trials clinical trials study different interventions in patients usually in the form of new vaccines or medications to determine which treatment is more effective in clinical
practice one of the first steps is identifying eligible patients which is both time and resource consuming since researchers must design and print brochures and manually screen clinics for LG patients with access to medical records AI can quickly identify which patients fit the right criteria to streamline the process in addition AI has already proven effective in the development of new treatments the first step in certain
clinical research is discovering possible drugs however despite extensive lab testing the discovery process can result in a waste of valuable time and resources many drugs that are effective in a lab fail in human trials Verge genomics was one of the first companies that discovered a potential drug for a myotrophic lateral sclerosis also known as ALS or Lou Gehrig’s Disease by using AI instead of animal or cell testing
instead of cell or animal data they used AI to analyze human data points to provide researchers with more accurate representations of effective treatments in humans this avoided the risk of drug failure when translating animal studies to human trials if you’ve experimented with chat GPT you’ve experienced ai’s writing capabilities first hand while these AI writing tools are far from perfect they can significantly reduce the time needed to prepare and revise manuscripts chat GPT has been used in scientific
research and has even been credited as a co-author on multiple papers however it’s not without its limitations including the hard to ignore fact that it can reference incorrect data and create fake citations other software such as consensus can be used to guide your initial literature review and provide summaries for papers that answer your research question don’t expect these tools to take over your academic writing just yet however they can catch grammatical errors brainstorm ideas and collect and
How AI Assists in Drug Discovery
synthesize data we dug into the possibilities and drawbacks of using AI writing tools in another video on the future of medical school applications if you think you can exclusively rely on chat gbt for your medical school or residency applications think again the Third Way AI is improving medicine is by streamlining administrative tasks in healthcare for example botmd is a company with an AI service that assists patients
with clinical issues like finding Physicians on call Scheduling appointments or answering prescription related questions such as the availability of certain medications or their Alternatives allowing AI to take over these tasks can free administrative staff to focus on other obligations AI can also simplify medical scribing since Physicians don’t have to take their own notes or employ medical scribes
as opposed to human scribes who are subject to human error AI Works instantly and immediately understands medical terminology AI technology can pre-authorize insurance and optimize billing for Physicians since billing is reliant on accurate consistent documentation reducing the burden of these tasks can help prevent physician burnout a significant problem that leads to psychological distress for
doctors and worse outcomes for patients lastly AI is quickly being integrated into medical education at all levels of training for example Oscar an Australian medical education company allows medical students to practice their history taking skills on AI patients using this tool students can learn to ask the proper questions and consider various diagnoses for any specific presentation integrating AI more thoroughly
into formal medical curricula can prepare future Physicians for ai’s increasing role in healthcare some universities like Duke and Stanford have already introduced courses to help medical students and residents learn to use AI to solve Health Care issues the Mayo Clinic and Stanford offer courses that teach
Remote Patient Monitoring Through AI
Physicians how AI is currently influencing medicine as well as how they can use it to their advantage in their practice AI is even influencing the medical school application process which we made a separate video about Link in the description AI has huge potential to revolutionize many different facets of medicine but with any change we should be cognizant of any drawbacks or possible biases we could
be introducing AI after all is designed and programmed by humans so it’s susceptible to the same biases we are as AI technology rapidly evolves in all areas of Our Lives from medicine to personal Wellness to writing we’ll continue to cover emerging topics here on our YouTube channel and the med school
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medschoolinsiders.com forward slash newsletter or visit the link in the description thank you all so much for watching if you enjoyed this video check out the top 10 most stressful jobs in healthcare much love and I’ll see you there foreign .
