12 Jul What Physicians Should Know About AI and Machine Learning in 2023
As we move into mid-2023, artificial intelligence (AI) and machine learning (ML) are increasingly being used in healthcare to improve patient outcomes, streamline processes, and reduce costs.
The role of AI and ML in healthcare continues to grow, with the potential to significantly impact the way doctors work – improving healthcare by streamlining diagnoses and improving clinical outcomes.
And while the adoption of AI in medical facilities has not been immediate, it’s gaining momentum in 2023. The FDA has been accelerating approvals of medical artificial intelligence tools – authorizing hundreds of devices over the past several years. As more devices are approved, more providers are weaving AI into their operations for uses in revenue cycle management, clinical decision support, and patient engagement.
Machine Learning in Healthcare
While many types of artificial intelligence exist, certain ones are more applicable to the needs of the healthcare industry. Machine learning focuses on streamlining medical administrative systems (such as health records), finding trends in large clinical data sets, and creating medical devices to assist physicians.
ML is an application that involves programming computers to collect and manage patient data, identify healthcare trends, recommend treatments, and more. Hospitals and health organizations have begun to recognize the ability of machine learning to improve decision-making and reduce risk in the medical field.
The most common applications – and the ones that show the most promise moving forward for physicians – are centered around improving the quality of care and patient health outcomes. Some examples of these benefits include:
- Accelerating Drug Discovery: For generations, the process of drug discovery has been a time-consuming and tedious process. But by predicting drug behavior, AI has the potential to make drug discovery more efficient and cost-effective, reducing the need for extensive lab work.
- Visualization of Biomedical Data: Practitioners can use machine learning to create three-dimensional visualizations of biomedical data such as RNA sequences, protein structure, and genomic profiles.
- Improved Diagnosis and Disease Identification: Doctors are able to identify previously unrecognizable symptom patterns and compare them with larger data sets to diagnose diseases earlier.
- More Accurate Health Records: More hospitals and practices are using machine learning to keep patient records updated, accurate, and easy to transfer between clinics, physicians, and staff.
- Enabling Personalized Treatment Treatments Many doctors and clinicians in 2023 are using machine learning to analyze multi-modal data and make patient-tailored decisions based on all possible treatment options.
- Improving Medical Research and Clinical Trial: Healthcare professionals can use machine learning to enhance the selection of participants for clinical trials, data collection procedures, and analysis of the results.
- Enhanced Development of Medications: You can use machine learning to identify potential pathways for new medicines by developing innovative drugs to treat varying medications.
A Final Word
Artificial intelligence will continue to improve healthcare approaches in 2023 and beyond – and has the potential to do much more. The growing use of AI in healthcare has opened up many ways to improve healthcare approaches for highly effective treatments. While still somewhat in its infancy, the acceptance of AI will continue to increase – offering physicians a wealth of opportunities to improve patient outcomes.
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