How AI’s Diagnoses and
Treatments are Improving Healthcare

Artificial intelligence is changing our lives, including how we live and work. It’s not only about AI doing jobs people used to do, but rather leveraging its power for tasks that people can’t do or would take forever to complete.

Analyzing large data sets and using machine learning to receive reliable information is one way artificial intelligence can serve a variety of industries. In this article, let’s examine AI’s power and potential to improve healthcare, including — but not limited to — diagnoses and treatments.

Clinical Practice in Cardiovascular Medicine:
How AI Can Help This Healthcare Sector

Some reputable healthcare facilities like the Mayo Clinic have already implemented AI in their working process. Here’s how they use AI’s power to assist doctors and scientists who specialize in cardiovascular medicine:

  • Detect a weak heart pump with AI-powered electrocardiograms. The clinic has millions of ECGs in the database, and a large existing set of information helps achieve the desired goal. In this case, after performing an ECG test, the artificial intelligence compares it to the database to identify a potentially weak heart pump in a patient. Thanks to this, AI can assist in predicting a risk of heart failure in the future and prevent potential heart problems.
  • Identifying abnormal heart rhythms before evident symptoms. Once again, ECGs driven by artificial intelligence serve to discover patients who might be facing this problem. AI could be capable of uncovering atrial fibrillation early and before symptoms appear.
  • Assisting patients who suffered a stroke. Intracerebral hemorrhage is a stroke that requires a CT scan. A doctor in the emergency room must schedule this scan, but a computer can analyze it and uncover essential data. This saves time when diagnosing the stroke, which can be an integral factor in reducing brain damage.

AI’s Healthcare Abilities Can Assist in Radiology Departments and Improve Patient Precision

Radiology experts best know how high their workload can get on certain days. The number of patients keeps increasing, but the need for consistent image quality remains. The idea is to leverage AI’s potential to enhance efficiency, which can be done in multiple ways.

Optimal patient positioning is the hardest thing to achieve when doing a CT scan. Not being in the proper position can expose the patient to a higher radiation dose than required and it can affect the noise level appearing in the images. A camera that uses AI can identify the patient’s anatomical landmarks. Thanks to that, it can ensure optimal patient positioning and make sure they reach that position quickly.

Artificial intelligence can also serve for better image reconstruction, which can enhance overall image quality. Apart from increasing the reliability of the diagnosis, this is how radiation dosage can be reduced, which can be vital for the patients.

Ultrasound and Magnetic Resonance:
How AI’s Making Healthcare Providers More Productive

Magnetic resonance is an imaging modality option that serves to reliably diagnose different medical conditions. An MR scan can shorten the way from the initial suspicion of a specific medical condition to the final diagnosis. But it’s not always easy for patients to undergo an MR scan. That’s especially true for those dealing with anxiety, stress, or pain.

Using image reconstruction with the assistance of artificial intelligence ensures the scan is done right the first time. That shortens the exam duration, making it easier to handle for a patient that might be wary of undergoing the procedure. The shorter exam time also means that more patients can do the scan per day, which improves the department’s productivity without compromising result reliability.

Ultrasound is another tool used in diagnosing certain medical conditions but also evaluating patient health. Although most patients undergo this imaging modality first, it’s far from flawless. Getting the right measures from an ultrasound can be complex and require significant time and effort from the person doing the exam. AI’s assistance comes in eliminating some repetitive and manual tasks. The machine can set automatic measurements to deliver fast echo quantification. Healthcare professionals can agree with the measurements or change them, which means they still have the final say in the entire process.

How To Use AI’s Potential To Streamline Patient Flow in Healthcare Facilities

Many hospitals have a significant turnover of patients, but the capacity of beds, equipment, and other resources is often far below the sufficient level. It’s why the staff is often forced to make tough decisions on which patients to prioritize. Even the most experienced healthcare provider will need to manage large amounts of data and dedicate time and effort during the decision-making process.

That’s where artificial intelligence comes into play. AI can analyze historical and real-time hospital information to discover relevant patterns. Thanks to that, the machine can deliver actionable info that the hospital staff can use when deciding on their actions. For example, which patient should have an advantage when it comes to getting a bed in the intensive care unit? Is any other patient ready to leave the ICU? With AI having more healthcare data to analyze, it will become more reliable in predicting patient flow, ensuring that every person receives optimal care at the correct time.

AI’s Influence on Healthcare Inclusivity

AI has become imperative to inclusive healthcare and help in multiple ways, with some examples listed below:

  • Speech-to-text applications. These AI-driven apps can improve communication between a patient with hearing issues and healthcare providers. It ensures the information is conveyed the right way, which can improve overall healthcare quality.
  • Virtual assistants. AI-powered assistants can help patients access relevant healthcare information and schedule doctor appointments.
  • Assist in underserved and marginalized communities. AI’s power to analyze vast amounts of data, such as health disparities and socioeconomic criteria, can ensure healthcare providers have more information in areas and communities that don’t offer sufficient resources for a reliable diagnosis.

How AI Can Reduce Healthcare Equipment Downtime

Large and expensive equipment, such as MR machines, are responsible for important jobs at healthcare facilities. Dozens of patients per day are examined by a single MR machine, making this equipment extremely valuable in treating people. If a single device fails and there’s no immediate replacement, that causes delays, leading to many people not receiving examinations. The waiting time could affect the quality and success of their treatment.

Artificial intelligence can be leveraged to introduce a concept called predictive maintenance. AI’s capability is to remotely check hundreds of different parameters on healthcare equipment, depending on the machine. The information uncovered can show the parts that will require replacement soon or pieces that need minor maintenance.

Identifying small fixes before they turn into major repairs and acquiring replacement parts in time can be vital to ensure the equipment keeps working flawlessly, and it extends the product’s life span. The estimation is that AI can help resolve at least 30% of equipment-related problems before they cause any major downtime.

Combine the Knowledge of Providers and AI’s Healthcare Potential

The idea isn’t to replace doctors with artificial intelligence, but rather to use the power of AI to complement their knowledge. Artificial intelligence focuses on data analysis, checking large data volumes quickly, and delivering reliable information while eliminating the possibility of human error. That allows doctors to spend more time in direct care — discussing potential health issues with patients and having more time to offer advice. Ultimately, AI’s improving overall healthcare, and patients not only get better treatment, but they feel more satisfied with the quality of the services provided.