Being able to rely on a second brain programmed to perform tasks that require precision, analysis, and processing of a huge amount of data is a great gift. Artificial Intelligence and its capacity to emulate human abilities empower many industries, but the real difference is being made in healthcare. Let’s look at how AI is entering operating rooms and clinical diagnostics.
What are the conditions for encouraging the entry of AI into healthcare?
Such a complex and disruptive technology requires preparation for adoption that affects three contexts: the stakeholders with whom health care organizations relate; the employees who will need to be trained about data management; and the patients who will need to know about the new services and how they are delivered.
Defining, for example, guidelines for data entry related to clinical trials is crucial when one then wants to share databases with national and international health care organizations included in the network. The reference is to research and development institutes, ministries, or health regulatory bodies, but also to suppliers who will have access to data related to drug sales.
The same goes for health care professionals who will need to know the potential and use of Artificial Intelligence systems. Not only that, talent and experts who learn how to program the algorithms and configure the smart devices will also have to be hired. This transition is not easy for two reasons: Highly skilled AI personnel are not as widespread as one might imagine; also, bureaucratic hiring procedures in healthcare are lengthy, which discourages programmers who prefer to be hired by multinational companies.
Finally, patients who, in some cases, are still reluctant to go digital will have to become familiar with new technologies and new ways of delivering services or collecting and consulting data. For example, they will have to learn how to interact with health devices, perhaps wearables. Or download apps for electronic health record consultation to their smathphone. Over time, the benefits would become apparent, but in the initial phase, resistance to change must be overcome.
Medtech: the impact areas of Artificial Intelligence in healthcare
The main reason for companies to implement Artificial Intelligence solutions is related to the ever-increasing need to collect, process, and analyze data. But what are the data that need such advanced technologies in healthcare? For starters, all values are related to clinical trials; but also information inherent in the diseases themselves, from diagnosis to treatment; medical records and images; population data, and incidence and recovery statistics.
Whether useful for making predictions or needed in day-to-day management, data are an indispensable basis for making decisions. How can we reduce the time it takes to collect and transform data into useful information? By using Artificial Intelligence algorithms that work very well on multifactorial data analysis, where this information interrelates, leading to the creation of increasingly accurate predictive mathematical models. Here are specifically which activities benefit the most.
Self-medication, prevention and wellness
There are diseases that patients will have to live with for very long periods of their lives and that do not resolve within the walls of a hospital room but continue within the walls of the home. Not only that but there are also diseases that, thanks to prevention, can be caught in time and defeated without putting people’s lives at risk. These are the fields in which AI yields remarkable results: self-medication, prevention, and patient well-being. The support that technologies can provide to patients results in time savings for physicians and more effective monitoring for the person.
Think, for example, of devices that offer remote support to older adults living at home alone and suffering from degenerative diseases. Some are shaped like a watch to be worn comfortably. They are equipped with sensors, and they monitor the person’s movements and activities within the home while communicating with caregivers in real-time. When patients press the integrated care button, caregivers know exactly where they are and what action they perform. All this is possible through intelligent indoor location tracking, deep learning, and sophisticated predictive analytics.
Artificial intelligence in healthcare offers many advantages in minimally invasive surgery but especially in clinical data collection, processing and management. Click To Tweet
Diagnosis: how AI identifies pathologies
Medical research acts on two fronts: on the one hand, it enables the discovery of new drugs and cures for diseases that are already recognized and classified, and on the other hand, it identifies illnesses that are still unknown. When we enter the field of rare diseases, it happens that the correct diagnosis arrives after some time, and the patient is given alternative treatments for diseases that have symptoms in common. This happens because there are so many variables to consider when analyzing a sick patient.
That is why health care using digital and intelligent technologies dramatically reduces the risks of human error. In fact, AI algorithms perform multifactorial analysis on medical data to generate correct predictions. AI can draw from information from multiple medical experiences and not from the reasoning of a single specialist who is standing, face to face, with the patient and has limited time to provide a diagnosis. The match will be made across all related departments by entering the patient’s clinical data into AI software. The response will be much more reliable and with a reduced error rate.
Diagnostics: AI for more accurate analysis
Diagnostics is a process that encompasses a range of investigative methods and techniques useful to the physician in recognizing the disorder and arriving at a diagnosis. In this field, AI support can extract clinically relevant information from complex and diverse clinical datasets. The percentage of accuracy detected is much higher than that of the technician or specialist on duty.
This is because algorithms can process much more information than the human brain. By processing, for example, a lung x-ray with more than 100,000 x-ray images synthesized in the previously trained model, the margin of error is dramatically reduced, and the diagnosis will be much more accurate. Technically, this process begins with the training dataset using the lung-related images loaded into the database and performing an operation called inference.
Specifically, we are in the field of computer vision that enables:
- analyze and classify diagnostic examinations such as CT, MRI, and PET by simplifying management;
- improve images by reducing blurring due to patient movement during the diagnostic examination;
- detect abnormalities or any injuries quickly.
AI to support critical decisions
Even in health care, in the era of Digital Transformation and Data Science, the huge flow of data that activities produce daily is a significant problem. Specifically, in healthcare, physicians manage an ever-increasing amount of health data made up of digital medical records, biomedical information, and updated clinical studies.
Carving out time between patients to turn data into useful information for decision-making is an increasingly daunting task. The risk is eroding time from updating the skills that enable a practitioner to personalize care and ensure the patients have the best diagnosis to defeat their disease.
Artificial intelligence software, which can quickly process and cross-reference data, allows health care professionals to extract, in a short time, accurate information relevant to the request. In this way, they can focus on decision-making choices that will be based on evidence curated by medical professionals.
Returning to the patient with a rare disease, the moment the specialist queries a worldwide disease database, entering all the case-specific variables, the answers could arrive quickly and allow the physician to make the correct diagnosis.
AI enters the operating room and the care pathway
Having seen the support that AI-powered software can provide to medical staff, let’s look at how it can act directly on the patient and improve the patient’s course of care.
Starting from the development of new drugs to the patient’s complete recovery, AI supports the main stages of health care. The software can be installed on PCs but also become the brains of robots that flank surgeons in the operating room. Suitable for operations related to minimally invasive surgery, the robot does not operate alone, but the surgeon mechanically guides its arms.
What is the advantage? Increased precision and reduced risk factors. In fact, robots ensure a constant performance on which stress and fatigue do not affect. Obviously, the decisions to be made about the patient during surgery depend on the specialist on duty, but for precision tasks such as surgical sutures or incisions, the robot’s mechanical work ensures optimal results while also facilitating postoperative healing.
AI systems also allow for the personalization of treatments and reduced healthcare costs. Chatbots, for example, could be an excellent filter to reduce the number of inquiries that come to health care facilities by providing an initial answer to frequently asked questions or by allowing an online booking to be completed by improving the system for organizing and managing visits.
Many potentials of Artificial Intelligence are still untapped, but to open the doors now, in healthcare, to the entry of this innovation is to prepare the ground to accommodate the innovations it will generate.
