Technological advancements have taken a step higher with the use of Artificial Intelligence (AI). It is used in transportation, communication, finance, banking, and other industries as well.
Now, AI is beginning to take the lead role in the healthcare industry. Frost and Sullivan (2016) said that AI systems are expected to earn 6 billion dollars in two years. A recent review by McKinsey (2018) revealed that healthcare would be one of the industries that will involve around 50 cases of AI.
Uses of AI in Healthcare Today
Currently, AI is already showing promise when it comes to different medical processes. Below are some of the areas in healthcare where AI is now being developed:
- Radiology – AI Solutions are underway for automated image analysis and diagnosis. This development will highlight entertaining areas to radiologists, therefore, increasing efficiency and reducing human errors.
- Drug Development – AI can be used to look into the vast information of current medicines that can be redesigned to cure other critical diseases.
- Patient Risk Identification – AI solutions can analyze a patient’s medical history to give clinicians ample background when it comes to a patient’s risks.
- Triage Services – AI solutions can lead to a voice or chat-based interactions to provide fast answers to underlying medical issues.
Challenges of AI in Healthcare
1. Ethical Considerations
Ethics is a susceptible and vital issue when it comes to medical data. Patients entrust doctors and hospitals to keep their data safe because it is taboo to be sharing such sensitive information to the world.
Medical records are considered as personal data, and personal data is strictly protected. Using AI solutions requires a vast amount of personal data from patients. Thus it poses a lot of questions: Is it ethical for hospitals to share their patients’ data for these AI solutions? Does the hospital own the data of their patients? Who will be accountable if there will be a breach of security?
This dilemma poses a challenge between the balance of ethics, privacy, and technological developments.
2. Data Privacy and Patient Protection
Hospitals working with AI companies have been scrutinized for sharing their patients’ medical information. As the question of ownership is still under debate, both parties must make clear and sound guidelines on how they are going to protect patients and their privacy.
3. Data Quality
AI has been working well with other industries like GPS, aircraft sensors, etc. because data in these fields are accurate. But how is it going to work in healthcare where data are subjective?
For example, there is no specific structure when it comes to clinician’s notes, so it will be challenging to categorize and interpret these data. Patients might not also disclose accurate information.
People have been used to having someone talk and explain to them their medical conditions. Is the world ready to entrust their health to machines?
There are still a lot of issues that AI solutions need to conquer to achieve its vision for the medical community.
But one thing is for sure: the medical industry needs an innovation that can help them address medical needs better than they’re doing now.
AI has shown promising results towards the development of solutions that can alleviate the current problems of the medical industry. The fears of AI replacing medical practitioners are still baseless. Instead, it is better to think that working with AI can make the lives of medical practitioners better, and medical services can be delivered faster.
Health is an essential aspect of life. It should be emphasized enough. Thus, AI solutions must be proven and tested well before it will be used massively to ensure that no mistakes will be fatal.