Revolutionizing Healthcare with Artificial Intelligence

The application of artificial intelligence technology in healthcare services is proving to be? disruptive in nature and is set to redefine medical diagnosis and treatment. Artificial intelligence is solving several persistent issues relating to the accuracy and correctness of diagnosis in the healthcare industry. It is being applied for a range of health services like medical imaging, treatment, drug discovery, and advanced surgery that, in turn, improve the efficiency of the treatment being availed by the patients.

The AI technology analyzes large sets of medical data in no time and helps the professionals identify problem areas that could have been overlooked otherwise. Medical facilities and systems are becoming faster, smarter, and more efficient by leveraging AI technology. Along with methodical treatment, AI is ensuring that patients avail themselves of a cost-effective model.

Impact of AI in the healthcare industry:

-Improved Accuracy

The AI algorithm is designed to analyze a vast number of medical records, test results, and scans and derive a diagnosis out of them. It is quick and efficient in identifying minor differences in the patient’s records and bringing them to the notice of medical practitioners who may have missed them otherwise.?

-Predictive Analytics

The AI algorithms can identify the potential health risks that the patients may face in the near future. This ensures timely resolution and proactive measures in order to avoid any serious repercussions. This is one of the best advantages that the healthcare industry may derive from AI integration.

-Personalized Treatment

The AI guides the doctors to develop a personalized treatment plan for patients based on their medical history and present health condition. Several AI tools help the practitioners create a customised plan by taking into account the unique health condition and circumstances of the patient.

-Reduced Administrative Workload

By automating several administrative tasks like billing, coding, and analyzing big data, the overall administrative workload is minimized to a great extent. It also frees up the staff from performing redundant tasks and thus improves the efficiency of the healthcare system altogether.?

Some of the ways in which AI algorithms can help with medical diagnosis are through image analysis (by analyzing X rays, CT scans, and MRIs), medical record analysis (blood tests, diagnosis test reports), symptom analysis (by studying the symptoms that the patient is exhibiting), etc. This set of data provides an overall analysis of the patients’ conditions, based on which the AI powered tools can derive a conclusion about their health. These factors determine the parameters based on which AI tools work.?

Types of AI technologies for Healthcare Industry

Let us look at the primary technologies that make AI more effective in healthcare industry-

Machine Learning: ML in healthcare helps in identifying medical precision and predicting which treatment would suit the patient more. The predictive analysis feature of AI is because of dominant use of ML in the form of deep learning. It helps predict the outcomes and analyze whether it can be effectively applied in a particular patient’s case.??

Natural Learning Processing: Application of NLP helps in speech recognition, translation, and text analysis. When applied in healthcare, they help in creation and understanding of clinical documentation. It also helps in accessing unstructured data about the patients and analyze reports in accordance with it.?

Robotic Process Automation: It is budget friendly and easy to access and performs structured administrative tasks. RPA relies on combined workflows and business rules that work like semi-intelligent consumers of the technology. In healthcare, they perform tasks like user-authentication, updating of patient records, billing, etc.?

Some of the popular job roles in AI for Healthcare are Healthcare Technology Consultant, Healthcare Project Manager, AI Scientist, Data Engineer, Strategy Consultant- Pharma, Product Manager- Digital Healthcare and Deep Learning Scientist- Medical Imaging.?

Although there may be some drawbacks to AI integration in healthcare, such as security and privacy concerns, a lack of human oversight, limited data availability, and technical challenges that practitioners may face. However, these factors can be worked upon in the coming years, and the upsides of using AI in healthcare outweighs these challenges.?