The use of Artificial Intelligence (AI) in the health sector is still evolving by providing new approaches that improve the delivery of care and health administration. AI takes the middle position in the increasing healthcare requests; it solves these issues with the help of better diagnosis, personalized treatment, and administrative work.
Healthcare is one of the largest industries in which the AI adoption rate is steadily increasing because of its ability to reduce expenses and improve the services being provided. As per a study by Statista, AI may help minimize time spent by doctors and nurses on administrative tasks which in turn could be spent on patients. The research giant further quotes that in 2021, artificial intelligence (AI) in the healthcare market was estimated at around US $11 billion worldwide and the forecast is that it will reach almost US $188 billion by 2030 making a CAGR of 37% for the said period.
AI in healthcare has revolutionized the sector. Tech giants have come up with readymade solutions on the cloud where corporate hospitals can simply subscribe and leverage the benefits of automation. In particular, healthcare SAAS AI trends show that the technology is taking the entire world by storm with its top-notch technologies and benefits. It is shaping the health tech sector through facets such as improved diagnostic imaging, accelerated drug development, enhanced patient monitoring, and others.
In this blog, we will see some top applications of AI in healthcare along with their use cases. Let’s get started.

What Does AI in Healthcare Mean?
Artificial intelligence has made its way into almost all industry sectors. The latest AI trends are noticeable in all fields leaving no niche market. However, AI in healthcare refers specifically to the use of computers to mimic the human brain in evaluating, interpreting, and coming up with decisions from health-related data. AI has become more prevalent in the healthcare sector in the recent past. For instance, machine learning is being applied in anticipating patient status, early identification of diseases, and even in individualized treatment.
According to a report from Accenture, AI could generate up to $150 billion in overall value added to the US healthcare market by 2026. This exponential rise shows the extent of change that has happened across the various fields in healthcare.
Further in the blog, we will see how AI can be used in healthcare and how it will impact the future.
5 Benefits of Artificial Intelligence in Healthcare
The following are the important benefits of using artificial intelligence in the healthcare industry. These effects include the improvement of processes, reduction of errors, and the provision of insights that help to improve patient care and productivity.

Enhanced Diagnostic Accuracy: Diseases such as cancer and heart diseases can be diagnosed at an early stage with the assistance of AI and the medical images and data of the patient.
Personalized Treatment Plans: AI helps in building patient-specific plans for increasing efficacy and decreasing adverse reactions to the treatment.
Operational Efficiency: It automates simple clerical work such as scheduling, billing, and documentation in the healthcare sector to reduce the stress of the employees and minimize mistakes.
Predictive Analytics: AI in medicine development can be used to analyze potential admissions, diseases, and resource utilization to ensure that healthcare organizations are ready and prepared.
Improved Patient Monitoring: Wearable technologies and remote monitoring devices with AI incorporated to allow the patient’s health status to be monitored continuously and chronically ill patients to be cared for routinely.

How Does AI Address Challenges Across the Healthcare Industry?
AI solves several problems that have been rampant in the health sector for a long time. Its biggest strength is in its capacity to take in and analyze large quantities of information within a short period. This capability improves the accuracy of diagnosis in medical imaging through the early identification of diseases and their treatments. In addition, AI helps to modify therapies based on individual patient characteristics and previous response patterns.
Apart from enhancing the clinical results, AI has an essential role in handling Electronic Health Records (EHRs.) It does this by minimizing the amount of paperwork that needs to be done while at the same time making data entry, retrieval, and analysis much easier and more accurate.
The use of AI in healthcare also helps prevent healthcare fraud and keep track of unusual patterns in claims and billing to prevent loss and maintain regulatory compliance.
Here are some ways AI is being used:

Automating tasks
Improving diagnoses
Predicting health risks
Personalizing treatment
Managing resources
Reducing errors
Improving Accessibility

Top AI Use Cases for Healthcare
AI and healthcare, together, can create magic in the realm of patient care. Combined, they have many use cases; let’s explore the top 10 use cases of AI in healthcare:
Precision enhancement in medical imaging
Through such applications, AI helps to improve the accuracy of diagnosis by medical imaging technologies like MRI, CT scan, and X-rays. There are various forms of imaging, and the human eye cannot decipher small differences that machine learning models can pinpoint. It also helps in early diagnosis of diseases such as cancer to facilitate early and effective treatment. For example, AI can diagnose tumors at an early stage and increase people’s chances of survival to a great extent.
Personalized treatment adaptation
Personalized medicine is an upcoming concept, and artificial intelligence is leading this concept. AI also applies big data analysis where patient information such as genetic makeup, lifestyle, and past treatment history can be used to come up with personalized treatment plans.
Such an approach guarantees that patients are given therapies that will be most useful for their conditions, thus reducing adverse reactions and improving the general treatment results. For instance, AI can assist oncologists in identifying the optimal chemotherapy for a cancer patient depending on the patient’s genetic makeup. Most healthcare businesses aim to provide the best and most personalized services to their patients.
Electronic health records management
It is crucial to acknowledge that general management of Electronic Health Records (EHRs) can be rather challenging and prone to mistakes. AI simplifies and accelerates data entry and data exchange while minimizing the chances of human error.
Clinical notes can also be mined by natural language processing (NLP) algorithms and patient data can be updated seamlessly. This not only saves time but also helps to provide healthcare providers with the latest and most reliable patient information, which is vital for further treatment.
Healthcare fraud detection
Another excellent use case of AI in healthcare is fraud detection. AI is a significant factor in detecting fraud cases in the health sector. Based on patterns and deviations in the claims and billing data, Artificial Intelligence can indicate transactions that require further verification. Through subsequent data, machine learning models can make adjustments to their precision to accurately prevent fraud before causing great monetary loss. This helps to avoid wastage of resources and also helps the healthcare service providers to abide by the set laws and regulations.
Remote patient monitoring
Telemonitoring is an essential aspect of care delivery, particularly in the case of chronic illness management. Smartwatches and other wearable technologies can monitor patients’ physical conditions, including pulse, blood pressure, and glucose levels, 24/7. These devices send information to the healthcare providers in real-time supporting interventions in case of abnormalities. For example, an AI system can notify a doctor if the patient’s heart rate is abnormal, allowing early treatment and avoiding adverse consequences.
Drug development acceleration
The entire process of drug development is extremely time-consuming as well as expensive. AI expedites this process by estimating the therapeutic effects and toxicity of the new drugs through enhanced computational models and analysis.
The future of drug development is quite bright. But how can AI help in this form of healthcare? AI can predict potential drugs and even improve clinical trial methods, thus saving time and money in the development of new drugs. This can result in quicker development of life-saving products for the patients. This also creates a nice business idea where investors can look forward to a better future.
To get started with your personal AI healthcare apps, you can look for the best AI app development companies.
Medical history record management
The record of patients has to be managed effectively in order to ensure quality care. Compared to human intelligence, AI systems are capable of processing huge volumes of past data and presenting a comprehensive picture of a patient’s condition. This involves compiling information from previous treatments, test results as well as genetic factors. Thus, a comprehensive and well-structured medical record can help identify the best course of action and improve the management of a patient’s care.
Genomic data interpretation
Analyzing genomic information is challenging, especially if one lacks experience in the field. AI makes this process much easier by examining genomes and defining which mutations and markers correspond to specific diseases.
Healthcare AI companies can apply these tactics to assess the risk of diseases, prevent their development, and create appropriate treatment courses. For instance, IoT improves the early detection of genetically inherited diseases such as BRCA-associated breast cancer.
Rehabilitation progress monitoring
Rehabilitation is an essential part of the healing process in cases of injuries or surgeries. Smart devices and applications can track the patient’s mobilization, strength, and other clinical factors over time. This constant assessment helps the healthcare providers to improve the rehabilitation strategy regularly according to the patient’s progress. For instance, AI can study the stroke patient’s gait cycle and suggest modifications to their physiotherapy schedule.
Hospital resource management optimization
The coordination of resources in hospitals is crucial to provide quality service. AI in the medical field enhances efficiency in the use of resources by anticipating admission, discharge, and staffing shortages. ML algorithms use past sales data and present trends to predict the need for beds, medical equipment, and staff personnel. This helps hospitals to deploy available human and material resources properly so that the patients can be treated within the least amount of time possible.
Clinical language processing
NLP capabilities of AI change the handling of clinical notes and documentation. When implemented to analyze large volumes of unstructured texts, AI systems can improve clinical decision-making and operational efficiency. For instance, an NLP system can provide automatic consultation summaries, call out important findings, and feed such information into the EHR without adding extra work for the healthcare institute.
AI-powered hospital asset tracking
Every hospital needs to keep track of the inventory possessed by the institution including equipment and other necessities. For this, AI in medicine and healthcare, integrated with IoT devices allows tracking these assets in real-time, guaranteeing they are available whenever required and minimizing the chances of loss due to their disappearance. This increases the overall productivity of the health facilities especially in the delivery of health care services to patients.
Medical documentation streamlining
Chart completion is a time-consuming activity, especially among healthcare providers. AI helps reduce the time spent on administrative work by transcribing and categorizing clinical notes. This saves time and enables healthcare providers to dedicate their time to patients. For instance, speech recognition can capture the doctor-patient conversation and record it on the patient’s file instantly.
Automated collection of patient-reported outcomes
Gathering data from patients is critical in evaluating treatment efficacy and the level of satisfaction. Most AI systems work with mobile applications and wearable devices to collect data from patients. These data are processed to inform treatment outcomes and patient status, enhancing the quality of care and patient satisfaction.
Solutions for staffing challenges
Lack of staff is a well-known issue in the healthcare organization. AI technology in healthcare solves this problem by improving workforce management and anticipating the required number of staff in accordance with patients’ traffic and previous experiences. With the help of such models, top candidates for open positions can be selected, so that healthcare facilities are properly staffed to address patients’ needs.
Healthcare AI Companies at Your Service
The adoption of technologies such as AI and machine learning in the healthcare industry can only bring positive changes for both the patients and the healthcare facilities. Generalizing accurate diagnoses, customizing treatments, easing administrative work, and managing resources, AI solves major problems and forges the future of healthcare. You can have a list of the best AI development companies from all over the world that excel in building personalized care for patients through bespoke solutions.
Contact these big players and talk about strategic planning that needs to be done. You may take into confidence the main stakeholders and opt for constant evaluation of the implementation of AI technologies in healthcare. In this way, you can fully realize the potential of AI and make progress toward a future as technology enhances the quality and availability of healthcare.

Derek Cohen
  |  Jul 5, 2024

Analyzing business activities and data to formulate the best business development ideas is where I earn appreciations and remunerations. I’m an ardent reader, business adviser, gadget aficionado and an amateur yet an avid writer. My urge for innovative writing evokes every time I come across new gadgets, neo technology and novel technical events.

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