Machine Learning in Medical imaging: automated feature extraction in diagnostics
Machine Learning (ML) algorithms focused on medical image analysis have revolutionized the diagnosis process. Now doctors can detect more diseases than previously. For example, more genetic illnesses can be recognized, which were not diagnosed before. Other diseases, such as Asperger’s or Parkinson’s can be detected better by ML-based facial recognition solutions.
ML-based algorithms that analyze medical images are bound to have a positive impact on different diagnostic fields. Let’s talk about some most popular areas:
Pathology. Microscopy and cytology are used for the early diagnosis of bladder cancer.
Dermatology. A pigmented lesion can be evaluated for diagnosing melanoma.
Ophthalmology. Early stages of diabetic retinopathy and cardiovascular disease can be diagnosed by examination of the retinal vessel.
Radiology. ML focused on medical imaging is immensely useful in Radiology as well. Algorithms allow a physician to archive better visibility of minor changes in cells and recognize unhealthy cells. It offers a possibility to detect early-stage cancer. In some cases, unnecessary tests can be avoided as well. For example, statistics of the American Cancer Society from 2017 show at least one false-positive finding in the results of about 50% of the women who get annual mammograms over a 10-year period. Besides the obvious side effects such as anxiety and physical discomfort, it often leads to additional tests that are not needed.
A new quality of medical treatment
Using ML methods by analyzing medical images a human physician can significantly improve the quality of medical care.
There are many possibilities, how automated and high-precision feature extraction can support healthcare organizations in everyday life. Here are only some of them:
Medical treatment can be personalized and matched to the individual characteristics of a patient. Having a more complete picture of the patient’s medical data physicians can develop a more effective treatment. Now doctors can choose diagnoses or avoid risks not only after analyzing the medical history of each patient but using prognosticative abilities of ML as well.
Analyze lifestyle and behavior for preventing illnesses
ML algorithms can support physicians in giving better advices about behavior and lifestyle to improve patient`s health.
Cut down drug production costs
ML can make pharmaceuticals drugs more affordable by reducing time and costs for their production.
Optimize the clinical trial process
Clinical trials can become cheaper but still be accurate. Algorithms can find clinical trial candidates by comparing data from medical history records. ML solutions can monitor the process of the clinical trial, track results, etc.
Allow robotic surgery
Medical imaging is very helpful in the field of robotic surgery as well. It allows doctors to operate more precisely and minimize risks.
Predict and model epidemics
ML algorithms can suggest the regions where epidemic outbreaks are possible soon by comparing information taken from satellites, different social media, and other information sources.
Medical Image Analysis solutions ready to use
While diagnostic confidence never reaches 100%, combining machines plus physicians reliably enhances system performance. The computerized module for detecting abnormalities in marked regions of medical images is extremely important. For example, Detector for COVID-19 and other lung diseases is a new machine learning solution that can help to improve the diagnostic process. With this solution, doctors can recognize a lot of diseases very quickly. Detector for COVID-19 and other lung diseases is an application that can analyze CT/MRI images in png, jpeg, or DICOM files format. The solution helps the doctors to classify about 14 different diseases such as Bacterial Pneumonia, COVID-19, Chlamydophila, Fungal Pneumonia, Klebsiella, Legionella, Pneumocystis and other viral types of pneumonia, ARDS, Pneumothorax, and Hydrothorax.
With a Detector for COVID-19 and other lung diseases, doctors can make the process of diagnosis easier, faster, and more precise. The solution offers better visibility of infected areas because they are highlighted. Detector helps to identify a particular disease more quickly suggesting diagnoses from the database. The algorithm calculates the probability of each disease in percentages. Doctors can share the received data with colleagues over a network to discuss the diagnosis. Detector for COVID-19 and other lung diseases is an important assistant when a lot of patients need medical help immediately, and time for each patient has significantly decreased. Because doctors spend less time on diagnostics, they can focus on the decision-making and treatment of patients.
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