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How Artificial Intelligence in Healthcare Changed the Medical Field: For the Worse, or For the Better?

Artificial Intelligence in Healthcare

In recent years, artificial intelligence (AI) and machine learning (ML) have changed our lives. In fact, it holds the potential to fully transform different industries and businesses. Many improvements in the medical field have been brought about by the use of artificial intelligence in healthcare.

In the medical field, artificial intelligence refers to the use of complex algorithms that are developed to automate tasks. It simplifies the lives of healthcare stakeholders by performing tasks that are usually done by humans. Also, the tasks are done in a faster and more accurate manner.

Artificial intelligence and machine learning have been used to find new links among symptoms of chronic illnesses. It has become so advanced that it can now be used to drive robots to assist in surgeries. The future of AI in healthcare looks pretty good. AI is improving healthcare through various machines that can do predict, understand, learn, analyze, and even act.

How is AI used in healthcare?

The uses of AI in healthcare are endless. Scientists have just started innovating healthcare processes with AI and there is still a lot to explore. As of writing, we have gathered some technological applications of healthcare that people should know about.

Accurate Diagnosis:

Incomplete medical records and the huge volume of data within a hospital’s system can lead to a lot of human errors. AI is immune to these variables. As a result, it can study the data in the system, and predict and diagnose a certain disease faster than most healthcare professionals. Machine learning and AI technology can be a big help for pathologists to make more accurate diagnoses.

AI is used to efficiently diagnose and reduce errors in diagnosis. Six years ago, errors on the diagnosis of illnesses and other medical errors caused 10% of all the deaths in the US. With the use of AI, the process of diagnosis has been improved. Furthermore, it has lessened the number of medical errors and incorrect diagnoses.

Drug Development:

Artificial intelligence is already widely used by many pharmaceutical companies to develop and improve medicines. The long and tedious process that comes with the discovery of new drugs up to their release in the market has also been improved, thanks to AI.

Furthermore, AI can play a significant part to fully incorporate newly developed drug. It will help pharmacists to make more informed decisions which will lead to the faster manufacturing of high-quality drugs, not to mention the consistency of every batch manufactured.

Currently, there are no drugs on the market that are developed with AI technology, but there is no doubt that it will be an invaluable tool for the development of more effective drugs and medicine in the future.

Clinical Trials:

The nature of how clinical trials are done in recent years is very problematic. Most of the clinical trials are done offline. They are managed with no integrated tools that can track the progress, gather the data, and the drug trial results.

Clinical trials are done to establish the safety and efficacy of a drug product in human beings for a certain disease. It usually takes 6-7 years. However, only 10% gain successful clearance, which leads to a massive loss in revenues. With the large volume of medical data readily available, AI can be leveraged to reduce failures in clinical trials.

Improvement of Patient Outcomes:

Through various strategies driven by artificial intelligence, patient outcomes can significantly improve. One of the main uses of AI in healthcare is to provide a better patient experience.

With the use of AI, hospitals will no longer need to employ data scientists. AI solutions can analyze and interpret a huge volume of data to assist medical professionals is making better decisions. As a result, patient safety and outcomes will improve, and the efficiency of medical services will increase.

Applications of Artificial Intelligence in the Hospital Setting

Aside from the many uses of AI in the healthcare industry, there are a few concrete applications of AI in the hospital setting. Both medical professionals and patients can make use of tools that are powered by AI.

Decision Making

In the recent years, application developers used AI in making tools to assist doctors in accessing data that will help them make more informed clinical decisions. AI can accurately recognize the patterns of health complications, which will be great clinical decision support.

Data Management

Proper management of healthcare data is beneficial for both the healthcare provider and the patients. Through AI-powered applications, patients can schedule their doctor appointments and register without the need to line up in hospital lobbies.

On the other hand, AI can be used by healthcare providers to share and exchange data among disparate systems, to archive clinical data, and match patient records.

Healthcare Finance Management

AI can also be a useful tool in capturing medical charges, managing patients’ healthcare finances, and managing the healthcare providers’ revenue cycle. Through artificial intelligence and machine learning finances and revenues can be managed in an automated manner. There will be no need for lengthy processes and paper receipts.

With all the uses and applications of AI in the healthcare industry, we can conclude that artificial intelligence has changed the medical field in the best way possible. There may be challenges that may be encountered along the way, but with intelyHealth solutions (hospital management software), the challenges of AI in healthcare can be overcome.

According to a study by Johns Hopkins, the third leading cause of death in the US is medical errors, with heart disease and cancer as the leading two respectively. Some studies have shown that the adoption of EHRs has improved patient safety. However, poor medical records management can lead to errors in medication, incorrect diagnoses, treatment lapses, and worse, life-threatening scenarios.

The security of patient data may also be at risk. Patient records are confidential and contain highly sensitive information, and when an oversight occurs, the privacy of patients is compromised. Healthcare data breaches are rapidly increasing, which made patients lose their confidence in sharing their medical histories.

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