Artificial Intelligence Use Cases in Healthcare
Healthcare Virtual Assistant
The healthcare industry is gaining many advantages from using NLP and conversational AI. Within the next three years, the use of virtual assistants is expected to grow rapidly. AI in healthcare will assist in making symptom checking and triage quicker and more cost-effective. In addition, the hospital can immediately know which patients need urgent medical attention and which can wait for primary care.
Conversational AI helps patients and physicians choose an ideal appointment time and location and go there by car. As a bonus, it will also provide helpful recommendations. It can show patients how to prepare for a visit, including which process should be fast, what they should dress, and what they need to bring.
How can AI be used in healthcare?
Automated Scheduling
Companies in the healthcare industry will utilize automated scheduling. Thanks to technology, they can shift priority from retail to primary care. AI technology in healthcare will prepare a time and send notifications and reminders when schedules align. As a result, we will be successful in spending much less time and money on health services.
Integrating Omics, EHRs, and Wearables
Using EHRs and data from wearable devices, AI will integrate omics and biochemical studies, including metabolomics, genomics, and transcriptomics. Patient phenotypes might be differentiated using wearable data combined with omics data. And this data collection via pervasive sensing devices will continue to increase in importance. In this approach, artificial intelligence used in healthcare could play a role in the processing and synthesis of such multidimensional data.
Cancer Studies Documentation by AI
Artificial intelligence in healthcare makes studies easier
Determining whether a patient qualifies for the requirements for a clinical trial is time-consuming and involves identifying several variables about the patient. Additionally, reading the patient’s whole medical history is often necessary. It is estimated that less than 5% of patients meet the required requirements for these types of clinical trials, partly because of the difficulty of locating the necessary details in large amounts of unstructured data.
Seattle’s Fred Hutchinson Cancer Center implemented NLP in Amazon Comprehend Medical to swiftly and efficiently match patients with clinical cancer studies from vast amounts of unstructured clinical record data. Doctors could analyze around 10,000 patient records every hour using natural language processing to locate those who met the inclusion criteria.
Diagnosing and Managing Kidney Disease with AI
Through the analysis of unstructured data, doctors and nurses may better diagnose patients and create individualized treatment plans. During this period, a lot of customers are trying to measure this data so that they can structure it. Digital imaging data from radiology, histology, and even smartphone cameras are analyzed by AI and ML and used by nephrologists and other medical professionals to make diagnoses.
Data can be analyzed via images with the help of AI in healthcare
To get insights from unstructured texts, AI uses technologies such as NLP and data from structured lab results or data kept in electronic health records. To evaluate the arterio-venous vascular access that leads from the patient to the dialysis machine, the Renal Research Institute (RRI) leverages deep learning on photos captured with smartphones and tablets.
Within seconds, a user will decide based on the analysis performed by a convolutional neural network (CNN). A cloud-based CNN gets the images from the tablet or smartphone and returns the appropriate answer.
Read more: Artificial Intelligence in Robotics: Top 6 Use Cases and Future (2023)
Benefits of AI in the Healthcare Industry
Providing User-Centric Experiences
Using data on patients’ and medical professionals’ preferences, requirements, and opinions, artificial intelligence in healthcare may assist in tailoring care to each individual and keep them interested and engaged. For instance, by evaluating massive volumes of data, including patient records, photos, laboratory tests, and symptoms, AI may aid in the speedy and precise diagnosis of health conditions. Also, it can assist in determining which treatments are ideal for each patient, considering their unique traits and expected outcomes.
Caption: AI technology in healthcare can enhance customer satisfaction
Alt text: artificial intelligence in healthcare
AI technology in healthcare can enhance customer satisfaction
AI technology in healthcare provides virtual assistance, feedback, reminders, and support through chatbots, apps, or voice assistants to boost patient happiness and loyalty. Supplying them with interactive platforms and simulations may also improve healthcare professionals’ decision-making skills, education, and training.
Improving Efficiency
By automating and simplifying these tasks, AI may help healthcare organizations better use their resources, save money, and make fewer mistakes. Appointment scheduling, billing, coding, documenting, and reporting are just a few examples of administrative tasks that might benefit from using artificial intelligence.
Automated error detection and correction in patient medications is made achievable by innovations in AI, allowing for safer self-medication. In addition, it improves surgery safety since it allows doctors to operate in tiny spaces. Patient flow management is a further field where AI in healthcare might be useful by its ability to estimate demand and capacity and allocate resources appropriately.
Doctors can operate the hardest case with AI in healthcare
Connecting Disparate Healthcare Data
Data from many different sources, including health records, genetic information, habits, and environmental influences, may be integrated and analyzed using artificial intelligence. As a result, it may be easier to come up with unique concepts and find the latest data than it would be otherwise.
By speeding up and reducing the cost of trial and error, artificial intelligence in medical field can significantly impact by facilitating the development of cutting-edge drugs, technologies, and cures. Artificial intelligence’s ability to recognize patterns and trends in disease prevalence, risk factors, outcomes, and treatments can potentially enhance population health and public health policy.
Separated data can work together with artificial intelligence in healthcare
Challenges for Artificial Intelligence in Healthcare
The healthcare industry is investing more and more in artificial intelligence development services to handle many complicated tasks. However, the latest technology has some particular challenges that must be addressed.
Data Privacy
Artificial intelligence systems collect sensitive health data that might be violated without proper protection. In addition, adequate safety precautions must be implemented to prevent private patient information from falling into the wrong hands.
Challenges of AI in the healthcare industry
Patient Safety and Accuracy
When applying AI to healthcare, patient safety and accuracy issues are the highest priority. AI systems must be provided to spot patterns in medical data, comprehend the interconnections between various diagnoses and therapies, and provide effective, patient-specific suggestions.
Integration with Existing IT Systems
Integrating AI with pre-existing information technology systems may make things even more complicated for healthcare professionals since it is necessary to have an in-depth understanding of how the underlying technology works to guarantee that everything runs smoothly.
Physician Acceptance and Trust
Last but not least, the mainstreaming of AI in healthcare depends on the approval and trust of medical professionals. The AI system must inspire trust in doctors by giving them reliable instruction. For this reason, AI’s decision-making process must be made public so doctors can verify that it is based on the most recent and reliable medical evidence. The ethical use of AI systems that are not harmful to patients is only possible if they are utilized following government regulations.
AI technology in healthcare should be reliable
Government Regulations of AI
AI regulation will tighten in the United States and Europe as the Food and Drug Administration (FDA) determines which medical devices to approve. That’s a big step beyond the limits of medical decision support systems and into the world of medical devices. Companies working on medical AI must address this issue in this scenario.
