AI In Medical - II

Updated: Apr 13



This is the continuation of the Part 1


There are different applications of AI for diagnosis. These app uses AI to treat patient and give them review. Some of them are:

  • Babylon in the UK use AI to give medical consultation based on personal medical history.

  • Sense.ly has developed Molly, a digital nurse to help people monitor patients.

  • Amazon Alexa app used to give basic health information and advice for children.

  • AiCure app used to monitor the use of medication by patient.

  • Dutch company uses AI to highlight mistakes made during the treatment.

  • AI is also used for the patient having diseases related to brain.


There are many different types of clinical task to which expert systems can be applied:


Generating alerts and reminders. In so-called real-time situations, an expert system attached to a monitor can warn of changes in a patient's condition. In less acute circumstances, it might scan laboratory test results or drug orders and send reminders or warnings through an e-mail system.


Diagnostic assistance. When a patient's case is complex, rare or the person making the diagnosis is simply inexperienced, an expert system can help come up with likely diagnoses based on patient data.


Therapy critiquing and planning. Systems can either look for inconsistencies, errors and omissions in an existing treatment plan, or can be used to formulate a treatment based upon a patient's specific condition and accepted treatment guidelines.


Agents for information retrieval. Software 'agents' can be sent to search for and retrieve information, for example on the Internet, that is considered relevant to a particular problem. The agent contains knowledge about its user's preferences and needs, and may also need to have medical knowledge to be able to assess the importance and utility of what it finds.


Image recognition and interpretation. Many medical images can now be automatically interpreted, from plane X-rays through to more complex images like angiograms, CT and MRI scans. This is of value in mass-screenings, for example, when the system can flag potentially abnormal images for detailed human attention.


Cons of AI in medical field:


  • Some systems require the existence of an electronic medical record system to supply their data, and most institutions and practices do not yet have all their working data available electronically.


  • Others suffer from poor human interface design and so do not get used even if they are of benefit.


  • Much of the reluctance to use systems simply arose because expert systems did not fit naturally into the process of care, and as a result using them required additional effort from already busy individuals.


  • Computer illiteracy of healthcare workers is also a problem with artificial intelligent systems. If a system is perceived as beneficial to those using it, then it will be used. If not, it will probably be rejected.


  • AI in medical will help in numerous ways, whether for poor patients or for people who can not detect the disease or for the person who did not get appropriate medicine for the disease.



Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last, unless we learn how to avoid the risks.

- stephen hawking


#covid19 #coronavirus #aritificialIntelligence #AIinmedical

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