The Future of AI in Healthcare: 5 Key Trends for Medical Excellence

However, unlike other industries, healthcare deals with sensitive and complex data. This data challenge raises eyebrows, questioning whether AI will continue to be the favorite tech for healthcare or lose its grip. 

These future AI trends in healthcare hold all the answers. But before we dive straight into them, let's understand its current role in healthcare and medicine. 

The Current State of AI in Healthcare and Its Benefits

From using AI to improve patient care to finding new drugs, the healthcare industry is getting the benefits of AI in every way. Here’s a quick snapshot of it. 

AI in Imaging

AI is a real boon for radiologists, as it allows them to detect even the hard-to-notice medical anomalies from CT scans, MRIs, and X-rays. The results are far better and faster than those achieved with traditional methods. Sometimes, AI even surpasses human radiologists in identifying difficult medical conditions like tumors or small fractures. 

Genomic Data Analysis

In patient treatment and oncology, AI is exceeding the boundaries. It can customize treatments and therapies for each patient according to their genetic makeup.

Drug Discovery

AI is accelerating how medical researchers are identifying new drugs to treat existing conditions. It also helps biologists understand how different compounds will interact with each other, easing the process of assessing drug efficacy and risks. This also helps drug manufacturers produce new drugs on a large scale without any delay or losing money.

Patient Interaction

For hospitals with several branches, AI is reducing the burden on administrative staff while improving patient interaction. Chatbots and virtual assistants integrated into hospital websites and applications are trained to handle routine queries, schedule appointments according to doctors' availability, and provide health information at their fingertips. 

These uses of AI in healthcare are bringing long-term benefits such as

• Accurate and faster diagnosis leads to earlier patient detection and treatment.
• Enhanced treatment efficacy by personalizing treatment results and fewer adverse effects.
• Reduced time and cost in drug development, enabling quicker availability of new treatments and more efficient large-scale production.
• More efficient operations and enhanced patient experience.

Real Examples of AI Solutions for Healthcare

1. AI Transforming Medical Prescriptions

Reading handwritten prescriptions has always been a challenge for chemists and physicians due to the varied writing styles of doctors. This leads to errors when keeping track of medical records. 

AI can accurately read and digitize these prescriptions by enhancing the capabilities of OCR technology. 

2. AI Extracting Medical Insights

The Healthcare industry generates huge and complex data, some of which is hard to process. Data collected during medical conferences is one of them which carries valuable insights on drugs and their efficacies. 

However, this data is usually unstructured and presented as text-based notes or audio. Extracting insights from this type of data is even more challenging, but not for AI.

AI solutions can analyze both data types and give insights on drugs, which are mostly discussed during the conferences, their efficacies, and other parameters, such as why doctors widely prescribe them. 

3. AI Bot for Scheduling Appointment

Scheduling appointments is one of the challenging tasks for hospital administrative staff. They manually check the doctors' availability and constantly engage with patients to confirm the appointments.

An AI bot can cut this time and burden by promoting self-service in patients. Integrated with mobile apps and hospitals' websites, this bot allows patients to book, cancel, or keep track of appointments from their homes without calling the hospitals. Not just booking, it can also alert you about upcoming appointments or consultations.

The Future AI Trends in Healthcare

1. AI and Digital Twin

The digital twin concept will change how scientists test new drugs. Researchers can test them on a virtual model of a real human or organ to understand how medicines, lifestyle choices, and treatments will impact patients. 

These models are the real stimulation of the human body. Integrating AI with digital twin technology will help researchers reduce the false negatives and positives of new medical procedures and drugs. 

2. AI-Powered Robotic Surgery

The concept of remote surgeries, where doctors perform surgeries using robots, is still new. However, these robots require human assistance in cases such as image capturing. 

In the future, we may witness more advanced robots that do not require physicians' assistance to perform simple tasks like ultrasound imaging. This form of advancement will save physicians time and resources. 

3. Virtual Care Consultation

The future of AI in healthcare is very promising in virtual care consultations. For example, when patients describe their symptoms, AI can suggest specific treatments to the doctor based on keywords. It can also alert the doctor to any extra benefits the patient might have through their insurance. This leads to more focused care and better outcomes. 

4. Earlier Prediction of Life-Threatening Illness

The best use of AI in healthcare developments is saving patients' lives from diseases that are hard to predict early. One such condition is acute kidney injury (AKI), which takes the lives of millions every year. 

AKI is, however, not a direct condition. Rather, it occurs as a complication of another illness. But it can damage the kidney or lead to its complete failure.

Google's DeepMind, in collaboration with the US Department of Veterans Affairs, has experimented with AI to predict AKI in patients as early as 48 hours. This early prediction can prevent cases up to 30% in the patients. 

5. Mental Health Support

Making AI models more accurate and precise is just one aspect. These models must also be empathetic in their responses to the healthcare industry. Thus, the future focus of AI development companies is to create non-judgemental and empathetic companions. 

These companions can provide support and suggest the best therapies to patients with mental health issues. However, training them to understand patients' emotional and mental states will be challenging for AI model developers. 

Conclusion

The role of AI in healthcare developments is very clear. It will take patient care to a new level beyond the boundaries of hospitals. AI in the medical field will also open up new ways to detect diseases, predict life-threatening illnesses, and plan and deliver personalized care to patients. 

However, new trends will create significant challenges where protecting patients and medical data will be the top priority. By partnering with an AI development company having both technical expertise and domain knowledge, healthcare providers can take advantage of these new developments. 

Softude offers extensive expertise in developing AI models specifically designed for healthcare, emphasizing data protection and regulatory compliance. Connect with our specialists for consultation on AI implementation, development, or optimization of your existing AI solutions.