AI Innovations in Healthcare

AI Innovations in Healthcare

AI in healthcare is a hotly contested topic. There are many benefits and downsides to professionals and patients using AI health apps.

Polling shows only 64% of patients are comfortable going to AI for medical advice without the oversight of medical professionals. Meanwhile, professionals see the benefits in AI for clinicians and AI in hospitals and get a numerous examples of how AI is transforming healthcare.

Benefits of AI Solutions in Healthcare

The positive AI impact in healthcare cannot be understated, from improving diagnoses, to automating routine tasks so doctors can spend more time helping patients, and automating research to discover effective treatments, doctors need AI to optimize healthcare.

Here are just a few positive examples of artificial intelligence in healthcare:

• Medical Scribe AI technology can automatically take notes from any appointment and store them in a patient's record. The AI can then highlight important insights and organize a person's medical history to put less of a burden on a doctor to recall their patient's unique needs.

• AI can read imaging results better than humans, noticing smaller details and comparing them with larger data sets for more accurate diagnoses. With the guidance of a clinician, these AI models allow experts to catch early stages of a disease in their patients.

• AI for staff management can improve how emergency rooms and hospitals function. Predictive models can determine what kind of care for patients is necessary based on their health data, then change the way the staff treats them to give that patient more personalized care.

• AI chatbots can be used by clinicians to ask questions and share experiences, making the AI's machine learning based on large data sets made by medical experts.

• AI has the potential of diagnosing and resolving rare disorders in a patient that a medical expert may not have personally encountered before.

• Less invasive surgeries by AI-powered machines improve patient outcomes by operating around sensitive organs.

• Healthcare insurance fraud can be mitigated with AI developed for fraud prevention. Fraud like this increases consumer premiums and by decreasing the amount of fraud, we decrease the cost of the premium.

• AI can use predictive analytics to determine whether any environment has higher risk of disease outbreaks.

• Administrative AI allows for healthcare organizations to make tasks such as appointment scheduling, billing, patient outreach, and more, much easier.

• AI is being used in clinical trials to perceive virtual or real environments with inputs created by machines or humans.

• AI for mental health can provide patients with 24/7 counseling and monitoring that is personalized to their needs.

How is AI Helping Doctors

The benefits of AI listed above are transformative to the entire medical landscape. Doctors take advantage of many of these benefits using a variety of AI Apps. Those specific AI Apps are:

Ada: AI for symptom checking and diagnosis help.

Enlitic: AI that analyzes imaging to detect issues and provide insights.

Butterfly IQ: integrates AI into ultrasound technology for enhanced imaging.

Suki: Voice-activated AI assistant for administrative tasks.

Linus Health: AI-powered tools for personalized care and cognitive impairment.

Heidi Health: AI to transcribe notes and generate summaries.

Hinge Health: AI for physical therapy that creates personalized training regiments.

MyPlate: AI-powered nutrition tools.

WellDoc: Monitors chronic diseases with AI.

Downsides of AI and Automation in Healthcare

The list above shows a wide range of benefits to integrating AI that healthcare companies cannot ignore. There is more to using AI than simply the benefits though.

To paint the full picture of how AI is affecting healthcare, we also need to discuss the downsides:

• AI often lacks a human touch and emotional intelligence. Healthcare companies often resort to using undetectable AI software for their patient outreach or marketing.

• AI can potentially lead to inaccuracies and hallucinations when determining diagnoses. Algorithms and also data sets can be biased in favor of determining certain outputs over others. Legally navigating the responsibility for mistakes due to AI involvement is a nightmare in the making.

• Lack of professional oversight in complicated health issues can lead to patients making uninformed decisions.

• Integrating AI requires a large amount of change management which may include job displacement.

The Future of AI in Healthcare

Healthcare has yet to implement AI to its full potential as the world waits for the technology to advance far enough that everyone feels comfortable using it. Until then, we must all learn and get acclimated to the many benefits and risks of the technology so that we adopt such tools responsibly.

The future of healthcare may be murky, and we may not be sure which tools are used and how, but what we can expect is better and more personalized care for patients, elimination of routine small tasks that get in the way of care, and more powerful research methods that inevitably result in discovering new treatments.