Healthcare is changing in numerous ways thanks to artificial intelligence (AI). It is streamlining patient diagnosis, enhancing medical imaging, revolutionizing drug discovery, enabling precision medicine and transforming healthcare administration.
However, many fear AI may replace human doctors, especially in areas such as radiology and pathology where their skills are crucial. Fortunately, it is being used as a force-multiplier and a technological backstop to ease the burden on staff and improve outcomes for patients.
10 - Diagnosis Made Easy
Developing accurate diagnoses is one of the most crucial aspects of global healthcare systems. But it can often feel like searching for a needle in a giant haystack, with physicians flipping through multiple medical journals and analyzing complex data.
AI can streamline this process, helping physicians find the right diagnosis faster and more reliably. It can also be used to detect conditions and injuries in medical imaging, such as X-rays, MRIs, and CT scans.
It can even be used to develop a digital twin, which simulates patient outcomes and helps doctors choose treatment options that will work best. This technology promises to dramatically improve diagnostic accuracy and maximize hospital efficiency. It can also reduce time spent preparing medications, making it possible to treat patients more quickly and effectively. In turn, this could help save lives and minimize healthcare costs.
9 - Next-Level Medical Imaging
AI technology has been used to analyze medical images and data, identifying abnormalities earlier than traditional methods. This saves time, improves accuracy and enables doctors to treat conditions more effectively.
For example, AI software can detect early signs of a brain tumor, which can help physicians diagnose and treat the condition before it spreads. This allows patients to receive treatment sooner, and potentially saves lives.
In addition, AI-based software can reduce the amount of time spent on a case by performing repetitive tasks. This frees up time for clinicians to focus on patients with complex needs and complicated histories. However, it’s important to remember that the success of AI-based software depends on the quality and quantity of clinical outcomes data. Therefore, it is imperative to conduct extensive clinical validation of these technologies. Also, it’s important to ensure that the algorithms are designed without bias.
8 - Personalized Treatment
The effectiveness of AI tools in healthcare depends largely on patient engagement and adherence. Properly designed AI could help to reduce the number of medical errors that are made each year, ease the paperwork burden that is pushing doctors into retirement and fill the gaps in access to quality healthcare in remote regions.
However, a lack of understanding about how these systems work and their limitations can lead to unrealistic expectations and distrust. The industry must continue to address these issues through transparency initiatives, education programs and robust policies. This will help to ensure that AI can be used effectively to improve healthcare outcomes for everyone. It will also help to mitigate risks such as data bias, confidentiality and security. This is important to avoid creating discriminatory results that could negatively impact marginalized communities. This will contribute to a more equitable and sustainable world.
7 - Accelerating Drug Discovery
The pharmaceutical industry is becoming increasingly excited about the potential of AI to accelerate drug discovery. This is because the process of developing a new drug is notoriously slow and expensive. In fact, it can take 10-15 years to bring a new drug from a promising candidate molecule all the way through clinical trials. And only about 3% of drugs that make it to this stage end up being successful [100].
AI can help reduce the time and cost of this process. It can be used to search a vast database of molecules and find those with the best chance of binding to a specific target. It can also be used to prioritize candidate drug compounds and predict which will pass through clinical trials. This will enable companies to skip over dozens of rounds of costly experiments and focus on the most promising candidates.
6 - Virtual Health Assistants
Many people are familiar with AI-driven technology, such as Amazon Alexa, and use it to play music, answer questions, make phone calls and even control their homes. Healthcare is just one of the many fields that’s leveraging these assistants to improve patient experiences and boost staff efficiency.
For example, healthcare service providers like Harvard Pilgrim Health employ AI to root out insurance fraud. This is an enormous problem that costs the industry $100 billion each year.
Artificial intelligence can help identify fraudulent claims and expedite their processing, approval and payment. Using this technology in healthcare will save time, money and resources for everyone involved. It will also boost the productivity of healthcare professionals. This is especially important in areas with limited medical resources and a high number of fraudulent insurance claims. In addition, it will improve the lives of patients who live in remote locations and have access to minimal medical assistance.
5 - Robotic Surgeries
While some patients are concerned about robots performing surgery, robotic-assisted procedures are safe and effective. Surgical robotic systems use tiny incisions to create ports near the area of operation and insert miniature surgical instruments and a high-definition three-dimensional camera. From a console, the surgeon manipulates master controls to direct the instruments. The system translates these movements into precise actions inside the body.
These technologies can improve the surgical experience, including less incisions and faster recovery times, without replacing surgeons. Unlike other medical applications of artificial intelligence, such as DL algorithms for image classification or skin lesion detection, surgical AI relies on dynamic data from the patient and different devices in the operating room.
Hospitals want flexible, adaptable solutions that improve workflows rather than disrupt them. Thankfully, new robots that appear on the market do just that.
4 - Remote Patient Monitoring
With remote patient monitoring, patients can track their symptoms via apps and wearable devices. This reduces ER visits, prevents further complications, and keeps patients healthy at home instead of the hospital.
For example, some startups like Merantix are using deep learning to read CT scans and identify lymph nodes in the human body. This saves physicians time and money because it’s a tedious task that requires expert reading skills.
Other companies like Sesame connect doctors with patients on a cash-pay single-visit or membership basis, improving health-care affordability. The startup is also leveraging AI to automate notetaking and help clinicians be more productive. As a result, it will allow doctors to spend more time with their patients. This will be especially helpful for patients with chronic conditions and long-term illnesses. They will be able to spend more time with their loved ones and have better quality of life.
3 - Predictive Healthcare
Healthcare practitioners can use predictive analytics to identify and take action against signs of disease based on a patient’s genetics, lifestyle habits and other factors. This can help lower health disparity rates and improve overall quality of life for patients.
AI can also be used to detect and monitor disease trends at the population level. By analyzing data from EHRs, medical claims and radiology images, AI can identify patterns and predict when a disease will spread, allowing healthcare providers to take preventative measures.
Despite its many benefits, AI in healthcare faces some challenges. Interviewees stressed the importance of addressing liability and funding issues and establishing clear guidelines for how to develop and implement AI solutions. This would ensure that the right tools are available when and where they’re needed, improving both staff morale and accelerating the speed at which new life-saving treatments can reach the market.
2 - Streamlined Administration
Healthcare AI software solutions automate a range of administrative tasks, allowing healthcare professionals to focus on their patients. This helps lower labor costs and improves the overall patient experience.
AI technology can help streamline healthcare processes by identifying patterns in medical data. This can lead to better diagnostic accuracy and a personalized treatment approach for each patient.
Additionally, AI can help reduce healthcare fraud by detecting suspicious activity and anomalies in medical records. This helps to reduce the number of fraudulent claims, which in turn saves money and prevents the delays in payment that can cause patients to suffer.
1 - Overcoming Occupational Stress
Healthcare practitioners must juggle endless paperwork, patient care and data analysis. AI is a savior for these professionals, giving them the time to focus on patients and boost their productivity.
AI can handle tedious administrative tasks like appointment-scheduling, translating clinical details and tracking patient histories. It can also streamline more complicated and meticulous work, such as assessing medical claims. Hospitals lose $200 billion annually due to false or invalid insurance claims. AI-based software detects mistakes and halts fraudulent claims, freeing up vital human hours for processing and resolving legitimate ones.
As with any disruptive technology, there are hurdles to clear for AI to fulfill its promise in healthcare. Experts agree that more transparency and collaboration is needed between innovators and healthcare practitioners. This includes understanding how algorithms work, where the underlying data comes from and what biases may be present.
