AI in Healthcare: Use Cases, Latest Trends, and Many More

Last Updated
AI in Healthcare Use Cases, Latest Trends, and Many More

An Introduction to AI in Healthcare

Artificial intelligence in healthcare is gradually changing. AI plays a vital role in the ongoing evolution of healthcare throughout its diverse disciplines in the global economy as a whole. According to the Deloitte study, 85% of healthcare business leaders said their organization would increase their AI spending by 2023. The use of artificial intelligence in healthcare can literally improve the lives of patients, improving diagnostics and treatment, and assisting them in making informed medical decisions easily. The global healthcare market is expected to grow to $31.02 billion by 2025, from $2.4 billion in 2019.

In this article, we will discuss what is AI in healthcare, its popular use cases, benefits, the latest trends, and the future of AI in healthcare.

What is AI in Healthcare?

The use of machine learning (ML) algorithms and other cognitive technologies in healthcare is referred to as AI in healthcare. In simple terms, artificial intelligence is the ability of computers to mimic human cognition and to learn, think, make decisions, and take action. In healthcare, artificial intelligence refers to the use of machines to analyze and predict outcomes based on medical data. The use of patient data and other information can provide doctors and other healthcare professionals with a more accurate diagnosis and treatment recommendation.

A few examples of AI in healthcare include enhancing diagnosis, disease detection, health risk assessment, drug development, administration, and communication, as well as speeding up and improving these processes.

AI in Healthcare: Use Cases

1. Use of AI in Patient Treatment

Use of AI in Patient Treatment

AI-powered chatbots for mental health treatment

Healthcare organizations are using AI-powered chatbots and other tools to diagnose and treat mental health conditions like depression and anxiety. AI-powered chatbots and other tools are of great help in the healthcare sector.

Surgery assisted by AI (Robotic Surgery)

Surgeons are increasingly using artificial intelligence to perform complex procedures more accurately and precisely. Consequently, hospital stays can be shortened, recovery times can be sped up, and patient outcomes can be greatly improved.

Treating patients with personalized medicine

With AI algorithms, doctors can analyze large amounts of patient data and make more personalized treatment decisions. As a result, healthcare costs can be reduced and outcomes can be improved.

Easy and faster drug development with the help of AI

Drug development is being accelerated through the use of artificial intelligence. Previously difficult-to-treat diseases are now able to be treated easily with latest and effective drug development.

Monitoring patients remotely

After the pandemic, the trend of remotely monitoring patients has increased. The use of artificial intelligence reduces hospital readmissions and improves patient outcomes by monitoring patients remotely with the help of AI.

2. Use of AI in Healthcare Administration

Use of AI in Healthcare Administration

To reduce cost

As healthcare costs are rising, it has become a major concern for both patients and healthcare providers. The use of artificial intelligence can improve efficiency, reduce waste, and identify opportunities for cost reduction. A few examples of how AI can be used are for optimizing staffing levels, reducing supply chain costs, and improving patient flow.

Appointment scheduling

A scheduling system powered by artificial intelligence can reduce wait times and optimize patient appointments. It is possible to create an optimal schedule using artificial intelligence by taking into account factors such as wait times, patient preferences, and provider availability.

Medical billing and coding

The process of billing and coding for medical services can be time-consuming and error-prone. By automating the process, errors can be reduced and accuracy can be improved. Using artificial intelligence, healthcare providers can identify billing errors and fraud, which reduces costs and protects patients.

AI to detect fraud

Using AI algorithms, healthcare providers can detect fraudulent billing and claims, reducing healthcare costs and protecting patients. Analyzing large amounts of data with artificial intelligence can lead to the identification of patterns and anomalies that may indicate fraud.

AI in medical research and data analysis

AI can assist in analyzing large amounts of medical data, such as patient records, clinical trial results, and medical imaging data. Ultimately, this can improve patient outcomes by providing new insights and discoveries. AI can also help identify patients eligible for clinical trials, which can result in improved research processes.

3. Use of AI in Diagnosis

Use of AI in Diagnosis

AI applications for imaging diagnosis

Diagnoses are increasingly made faster and more accurate by using artificial intelligence in diagnostic imaging. Medical images such as X-rays, CT scans, and MRIs can be analyzed using AI technology. As a result, radiologists can make more accurate diagnoses, detect conditions earlier, and reduce the need for unnecessary tests and procedures.

AI for testing and analysis in laboratories

Using artificial intelligence, laboratories can analyze laboratory data, such as blood test results, to identify patterns and anomalies that could indicate certain conditions. As a result, doctors will be able to make better decisions about their treatment and monitor how well interventions are working over time.

AI and telemedicine

Telemedicine refers to the use of technology to provide healthcare services remotely. As part of telemedicine, AI can provide remote consultations with healthcare professionals, personalized medical advice, and assist in triaging patients. As a result, healthcare can be made more accessible in areas with limited resources or where it may be difficult to meet in person.

AI-based analysis of medical records

Using AI algorithms, for example, one can identify patients with a high risk of developing certain diseases based on their medical history. AI can help doctors make more informed decisions about diagnosis and treatment by analyzing electronic medical records (EMRs) to identify patterns and trends.

AI on diagnosis accuracy

According to a study published in the Lancet Digital Health, an AI algorithm can diagnose certain eye diseases as accurately as experienced ophthalmologists. A reliance on AI, however, may also lead to overdiagnosis or misdiagnosis if the technology is not used appropriately or algorithms are not validated. Therefore, it is important to continue monitoring the impact of AI on diagnosis accuracy and make sure that it is used responsibly.

Benefits of Artificial Intelligence in Healthcare

  • Improved diagnosis
  • Personalized treatment
  • Better clinical decisions
  • Serves rural communities better
  • Streamlines several processes
  • Helps develop drugs faster
  • Saves time, cost, and resources
  • Supports medical research
  • Improved healthcare staff productivity

AI in Healthcare: Top 5 Trends to Look for in 2024-2025

Top 5 emerging trends in AI in Healthcare to look for in 2023

1. Telehealth

AI technology is being used in telemedicine to enhance provider efficiency, maintain patient connectivity with wearables and other tools for remote monitoring, and even bring specialty care to remote areas previously unreachable. Disease diagnosis, health monitoring, and triaging are automated using chatbots and virtual health assistants powered by NLP.

2. Medical robots

Startups are building medical robots to deliver care in rural locations or carry out intricate procedures with more accuracy. Robotic surgery improves success rates and decreases problems, while telepresence robots replicate physical presence, and medical transport robots and drones with AI routing may deliver medical supplies and equipment autonomously.

3. Clinic trials

AI improves clinical trial efficiency by analyzing medical data and forecasting results. Additionally, it helps researchers find viable therapies and medications and optimize trial design. Startups are employing natural language processing (NLP) to create a holistic picture of patient health, allowing researchers to spot trends and negative events.

4. Personalized healthcare

Healthcare organizations are creating ML and deep learning models to obtain insights about variations in a person’s genetic makeup, way of life, and medical background. This makes it possible for medical facilities to provide specialized and personalized care. Additionally, startups offer platforms for testing and diagnostics that can identify diseases early, predict their risk, and evaluate the effectiveness of treatment.

5. Hospital management

In hospitals, AI automates administrative duties, addresses staffing issues like staffing shortages and staffing allocation, and improves operations and resource use. To maximize resource use and hospital operations, startups use patient flow management and AI-based predictive modeling. Software for supply chain optimisation and hospital management powered by AI offers targeted interventions and policies to raise the standard of care.

Challenges and Limitations of AI in Healthcare

Challenges and Limitations of AI in Healthcare

Despite the significant potential, there are limited AI-enabled solution adoptions in medical practice. In addition to privacy issues, AI technology also has methodological and technical flaws. The following are the primary challenges affecting AI in healthcare:

1. Lack of quality data

To validate AI models on a clinical and technical level, clinicians require high-quality datasets. It is challenging to collect patient information and images to test AI algorithms due to the fragmentation of medical data across several EHRs and software platforms.

2. Might create social biases

AI algorithms can be biased if they are trained on unrepresentative data or when it contains biases by design. Patient safety can be compromised as a result of unfair treatment of certain groups of patients.

3. Possible security risk

The primary and direct drawback of AI in healthcare is the potential for data privacy security breaches. Since it develops and expands based on information obtained, it is vulnerable to misuse and abuse. The hospitals that invested in AI will simply need to spend more for data protection, no matter how initially cost-effective the investment was.

4. Cost can be a barrier

The cost of implementing AI technology may require healthcare organizations to invest in new infrastructure, software, and experts. It can be difficult for small organizations to adopt the technology with a limited number of resources. Hence, it will create a barrier for smaller organizations.

5. Technical difficulty

It takes a high level of technical expertise to develop and implement AI technology. Implementing and maintaining AI systems can be a challenge for healthcare organizations due to a lack of an expert AI team. You can opt for the best AI software development services to easily implement AI technology in your organization.

6. Ethical issues

The use of AI in healthcare raises ethical concerns, including the possibility that AI systems can make decisions without human guidance. To ensure ethical and patient-centered AI use in healthcare, healthcare professionals and organizations must adhere to ethical guidelines.

Hence, implementing AI in healthcare is challenging and limited by a number of issues. Health professionals, AI experts, and policymakers must collaborate to make AI development and implementation effective and responsible.

Advance your Healthcare Services with AI

Although the application of artificial intelligence in healthcare is still in its early stages, more and more providers are beginning to realize how crucial this technology will soon be. To achieve a competitive edge, we advise healthcare providers to incorporate AI as soon as possible. But safety and quality of software are essential, particularly when it comes to healthcare, therefore businesses should pick dependable and knowledgeable AI experts.

Digitalized with our innovative healthcare software development services

AI in Healthcare: Unveiling the Future of Medical Services

There is still more work to be done in AI, but the future of AI in the Healthcare sector appears bright, achievable, and exciting. In the future, AI-powered solutions will play a crucial role in how healthcare systems operate, enhance clinical resources, and ensure patient well-being. AI-based treatments are more expensive, but once they are ready, they will provide a sophisticated, rapid, and effective diagnosis. Moreover, this will make training medical students easier and more interesting with realistic simulations that simulate real-time situations, which even computer-driven algorithms can’t provide.

Human clinicians will not be replaced by AI systems on a large scale, but rather, their efforts will be augmented. Human clinicians may eventually switch to tasks and job designs that require empathy, persuasion, and the ability to integrate big-picture thinking. Artificial intelligence is likely to replace only those healthcare providers who refuse to implement the latest trends in artificial intelligence.

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Niha Parmanandani

A dynamic content writer with a degree in Mass Communication and Journalism, she specializes in writing for web and social media.  It is her passion to play with words and keep up with technology trends. Her passion for reading drives her to create engaging, educational, and inspiring content.


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