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Applications of Artificial intelligence in the medical field & healthcare

Artificial intelligence tools are used in every area of healthcare, AI is used in doing repetitive jobs, Analyzing tests, X-Rays, CT scans, data entry, and other mundane tasks can all be done faster and more accurately by robots, Artificial Intelligence is used in decision support systems, When given a set of symptoms, DXplain comes up with a list of possible diagnoses.

Artificial Intelligence in Medical Applications

There are many applications of Artificial intelligence in the medical field such as Artificial intelligence techniques in medicine, Medical signal & image processing techniques, Medical expert systems, Machine learning-based medical systems, Data mining and knowledge discovery in medicine.

AI is used in laboratory information systems, Germwatcher is designed to detect, track and investigate infections in hospitalized patients, Robotic surgical systems such as The da Vinci robotic surgical system that comes with robotic arms, precise movement and magnetized vision, It allows doctors to make precision surgery that wouldn’t be possible with an entirely manual approach.

Artificial intelligence will have a big impact on the healthcare industry and the ways in which healthcare related companies utilize AI, Redivus Health is a transformative mobile app used by healthcare providers to prevent medical errors by offering both clinical decision support during critical medical events as well as documenting those events electronically in real time.

Artificial intelligence in diagnosis

Artificial intelligence in healthcare 

Echocardiograms can produce sound waves to paint the heart’s picture from which cardiologists can identify whether the patient has any heart disease, It’s a standard test to check for problems with valves or chambers of our central organ, for congenital heart defect or whether shortness of breath or chest pain in connection with the heart.

Between 2 and 3 million non-melanoma skin cancers and 132,000, melanoma skin cancers occur each year globally, Digital health technologies, such as smartphone apps like SkinVision, telemedical services as well as AI are at the frontlines of fighting widely prevalent diseases.

AI systems are used for the ICU, Intensive care units are battlegrounds for human lives, As every moment counts, patients are monitored 24/7 with an army of devices, Constantly beeping bedside monitors show blood pressure, heart rate or any other vital signs of the patient, The machine takes care of the function of the lungs as best as possible, and another goes for the heart, Although, these instruments are usually not connected, they are isolated units in the concert of ICU care.

Computers can detect breast cancer risk, the algorithm could support doctors with cases when breast density would not allow clear diagnosis, Artificial intelligence helps pathologists diagnose metastatic breast cancer, AI could not only assist radiologists but also pathologists in their fight against breast cancer, combining the efforts of the human pathologist and the deep learning system’s predictions, the human error rate decreased by 85 % when identifying metastatic breast cancer.

AI is used as virtual Nurses, Molly is a digital nurse that helps people monitor the patient’s condition and follow up with treatments, between doctor visits, The program uses machine learning to support patients, specializing in chronic illnesses, Some apps give basic health information and advice for parents of ill children, The app answers asked questions about medications and whether symptoms require a doctor visit.

Most applications of virtual nursing assistants allow for more regular communication between patients and care providers between office visits to prevent hospital readmission or unnecessary hospital visits, Care Angel’s virtual nurse assistant can offer wellness checks through voice and AI.

AiCure app can monitor the use of medication by the patient, A smartphone’s webcam is partnered with AI to autonomously confirm that patients are taking their prescriptions and helps them manage their condition, Most common users could be people with serious medical conditions, patients who tend to go against doctor advice, and participants in clinical trials.

Smart algorithms can predict suicide risks, some scientists aim for with their AI system developed to catch depressive behavior early and help reduce the emergence of severe mental illnesses, Machine Learning has made huge advances in automatically diagnosing diseases, making diagnostics cheaper & more accessible.

Machine Learning algorithms can learn to see patterns similar to the way doctors see them, Machine Learning is helpful in areas where the diagnostic information a doctor examines is already digitized, Such as detecting lung cancer or strokes based on CT scans, Assessing the risk of sudden cardiac death or other heart diseases based on electrocardiograms and cardiac MRI images, Classifying skin lesions in skin images, Finding indicators of diabetic retinopathy in eye images.

AI is used in diagnostics, Algorithms are becoming as good at diagnostics as the experts, The difference is: the algorithm can draw conclusions in a fraction of a second, and it can be reproduced inexpensively all over the world, Soon everyone, everywhere could have access to the same quality of top expert in radiology diagnostics, and for a low price.

The applications of Machine Learning in diagnostics involve the combination of multiple data sources (CT, MRI, genomics and proteomics, patient data, and handwritten files) in assessing a disease or its progression, Machine Learning can help discover which characteristics indicate that a patient will have a particular response to a particular treatment.

Robots can analyze data from pre-op medical records to guide a surgeon’s instrument during surgery, which can lead to a 21% reduction in a patient’s hospital stay, Robot-assisted surgery is considered “minimally invasive” so patients won’t need to heal from large incisions, Via artificial intelligence, robots can use data from past operations to inform new surgical techniques.

AI-assisted robotic procedure resulted in five times fewer complications compared to surgeons operating alone, The robot was used on an eye surgery for the first time, and the most advanced surgical robot help doctors to perform complex procedures with greater control than conventional approaches, Heart surgeons are assisted Heartlander, a miniature robot can enter a small incision on the chest to perform mapping and therapy over the surface of the heart.

AI can be used to automate administrative tasks, machines can help doctors, nurses and other providers save time on tasks, Technology such as voice-to-text transcriptions can help order tests, prescribe medications and write chart notes, AI depends on the power of computers to sift through and make sense of reams of electronic data about patients—including ages, medical histories, health status, test results, medical images, DNA sequences, and many other sources of health information.

Image analysis is very time consuming for human providers, AI excels at the complex identification of patterns in these reams of data, and can do so at a scale and speed beyond human capacity, There are many types of imaging tests such as X-rays, CT scans, MRIs, and echocardiograms, But the underlying commonality in all those imaging methods is huge amounts of high-quality data, For AI to work well, it’s best to have very complete data sets—no missing numbers.

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