By: Jiya Sood
A patient walks into a healthcare clinic, with vague–but severe–symptoms. Within minutes, they are given an accurate, quick, and helpful diagnosis, clear treatment plan, and quality healthcare support. This isn’t a scene from the future. It is the new frontier of artificial intelligence–a developing technology that is saving the lives of millions. Currently, AI is transforming from a minor medical assist tool, to an integral part of clinical technology in diagnostics, drug discovery and development, operational efficiency, and personalized treatment for patients.
There has been a significant transformation of diagnostic processes within health clinics, and this change is driven by several AI technologies. Some specific examples of recent AI technologies that have transformed diagnostics include…
- TREWScore, a targeted real-time early warning score
- This device analyzes physiological and laboratory data from ICU patients to predict if they will develop septic shock, a leading cause of death in the United States. This device can prevent lethal consequences for patients with immunity conditions and infections, or at risk for severe sepsis.
- Computational pathology
- Computational pathology is a field of medicine that uses artificial intelligence and machine learning to analyze digitized tissue samples and data from patients to determine cancer diagnosis and various other conditions.
- Recently developed AI-enhanced stethoscopes & ECGs
- These technologies have been used to detect cardiac disease at its earliest stages with greater precision.
- A new AI tool called Dr. CaBot, which spells out its reasoning as it works through challenging medical cases as it reaches a diagnosis. This system is extremely useful for medical education, because it breaks down difficult cases and arrives at an accurate diagnosis, along with a detailed explanation.
These recently developed methods improve diagnostic accuracy and speed, enhance early treatment plans for patients, and contribute further to significant advancements in medical usage of AI.
Artificial intelligence also drastically reduces the time, effort, and cost needed to identify, develop, and implement drugs and medication. One major issue with drug development is known as the “lock and key” problem. It prevents certain proteins from combining with a drug; therefore not allowing the drug to work properly and heal the body. Artificial intelligence has several ways to overcome this problem.
Generative models of AI, such as diffusion and Generative Adversarial Networks (GANs), create entirely new molecules that fit specifically into target protein pockets, speeding up the development and evaluation process of many medications. These systems pose several advantages to faster and more effective drug development, such as design precision, flexibility, speed, and efficiency.
Artificial intelligence also helps with operational efficiency within healthcare clinics. For example, AI is used for administrative and workflow automation, clinical support, and operation and resource management. These devices can include
- AI digital scribes, also known as the smart note-takers. This model listens to conversations between the doctor and the patient, transfers this dialogue into clinical action, and provides medically reviewed documentation for the patients. This new technology significantly reduces diagnostic, treatment, and documentation time, while also enhancing patient and doctor face-to-face communication.
- AI-powered 3D imaging tools, such as CT scans and HKUST 3D imaging, help create advanced 3D views of blood vessels in the brain and neck. Using this technology, physicians are able to quickly identify urgent issues in the patient’s body and areas affected by a potential stroke, says an article by Imaging Technology News. This allows for better, faster, and more efficient treatment for patients dealing with cardiac and nervous system issues.
Quality care is essential to good healthcare, and AI is also reshaping methods of patient management. For example, several chronic disease management technologies, such as smart insulin pumps, electronic inhalers, and AI-enabled smart pens, automatically adjust bodily settings based on real time readings and activity. This technology can improve accessibility and ease of use for many patients living with conditions like diabetes, asthma, and other long-term disorders.
AI technology is shifting medical treatments from a general process, to an individualized approach. For example, AI has played a significant role in the treatment of individuals fighting cancer. Due to the diversity and uniqueness of every body, and cancerous or genetic tumors, it is imperative for the treatment to be focused on the patient, and not have a “one size fits all” approach. Artificial intelligence tools such as the IBM Watson for Oncology analyze the patient’s medical history, genetic information, and relevant research to recommend the best tailored cancer treatments. Furthermore, by analyzing patients’ medical history, lifestyle, and family medical history, AI can predict the risk and likelihood for several diseases in their body, and create personalized precaution plans, like diets, lifestyle changes, and early screenings. This allows for more personalized care systems, benefiting patients, doctors, and clinics.
In conclusion, artificial intelligence has evolved from a supplemental medical assistant to a significant component of modern clinical and technical applications within the medical field. Groundbreaking discoveries can be made utilizing artificial intelligence in healthcare and medicine. By revolutionizing diagnosis methods, drug development, workflow optimization, and patient care, it is no longer a mere support tool, but a foundational component of many healthcare processes and technologies today.
