After the penetration of AI in different sectors, the world has never been the same. We have witnessed the usage of AI in predicting patterns in data, voice, and image recognition, and now, it is penetrating almost every industry. The healthcare industry is no exception. With the rise of digital technologies, there has been a development of various healthcare apps with advanced features & functionalities. People are now seeking healthcare assistance on mobile apps, and that’s why there is a high demand for healthcare app development companies.
AI is playing a big role in the healthcare app as well. Healthcare service providers can leverage AI and ML to create out-of-the-box healthcare applications. AI in the healthcare sector can improve operational efficiency and help the medical staff to deliver personalized and data-driven care. It will also help healthcare institutions to get an added advantage in the competitive industry. The healthcare industry now demands accuracy, efficiency, and personalization, which is possible through AI.
In this article, we will delve into various aspects of AI in healthcare app development, including its applications, benefits, and examples. Let’s begin with the basics.
What is Artificial Intelligence in Healthcare?
AI in healthcare apps refers to the usage of machine learning algorithms and cognitive technologies in medical apps. AI can simulate human intelligence and perform complex automated tasks. Ostensibly, it may seem AI can mimic human abilities, but it can also exceed in terms of sifting through large volumes of data to identify patterns, anomalies, and trends.
AI in healthcare can improve a myriad of medical processes, from diagnosing diseases to identifying the best treatment options for patients based on their medical history. IoT in healthcare is also paving the way for better treatment. The robotic surgical equipment is fitted with IoT devices and AI that help surgeons perform surgeries better. It can decrease their physical fluctuations and provide real-time updated information.
Type of AI Technologies in Healthcare App Development:
Generally, everything that seems automated is termed AI. In layman’s terms, it is AI, but if you are an entrepreneur who wants to use AI in healthcare, then you must have better clarity. There are different types of AI which are used in healthcare app development:
1. Machine Learning and Deep Learning:
ML is an interchangeable term with AI, but it deals with data. Deep learning is a subfield of ML, and it is used in healthcare research and predicting outcomes. In healthcare apps, ML is used to train datasets for better medical precision, i.e., treatment plans.
2. Natural Language Processing:
NLP, or natural language processing, can recognize human speech, analyze text, and translate accordingly. In healthcare apps, it can be used to comprehend clinical documentation research information and assist customers with conversational AI.
3. Robotic Process Automation:
RPA refers to the usage of AI to automate certain administrative tasks and clinical workflows. It is mostly used to automate repetitive tasks that don’t require human intelligence.
4. Predictive Analytics:
This subfield of machine learning and artificial intelligence in healthcare identifies patterns and connections in data to predict future outcomes. In healthcare, doctors, clinicians, and experts use this technology to determine treatment options based on symptoms.
Benefits of AI in the Healthcare App Development:
As medical institutions are leveraging AI to better deal with data patterns and effectively provide treatment, there are multiple benefits of AI in healthcare. These are some of the AI-based healthcare app development benefits:
a. Improve Accuracy in Diagnosis:
A doctor has to deal with tons of patients, so they can’t always go through a complete medical history of a patient. However, AI can. It can analyze large datasets of medical records, images, and diagnostic tests to assist medical clinics in accurate and timely diagnosis.
b. Personalized Care for Each Patient:
The data analysis is not just limited to accurate diagnosis but also helps provide personalized care to each patient. The data will be analyzed in the backend of the cloud and will provide accurate results. Personalization will lead to higher patient satisfaction, contributing to improved diagnoses and outcomes.
c. Administrative Tasks Get Efficient:
In hospital management systems and other interfaces, AI can automate tasks like scheduling appointments, managing medical records, and processing billing. Thus, the healthcare staff can work on more productive tasks.
d. Predictive Analytics Reduce Costs:
AI can help healthcare practitioners save money on healthcare by streamlining processes, decreasing medical errors, and promoting preventive care. By digitizing healthcare routines and transitioning to remote care models via telehealth apps, institutions may treat more patients per day with fewer resources.
Use Cases of AI in the Healthcare App Industry:
Whether you go for mental health app development or any other kind of healthcare app, AI will always have a use case. The complexity of the app and the type of healthcare app will decide the level of AI required. Here are some of the most prominent use cases of AI in the healthcare app industry:
a. Diagnosis and Treatment:
The data analysis capability of AI can be harnessed to analyze the medical history of the patients and diagnose the underlying disease. A perfect is IBM’s Watson for Oncology. It analyses the patient data for personalized cancer treatment, which helps in clinical decision-making.
WFO has arranged and cataloged patient charts, protocols, and literature. It has learned from specialists and test cases at Memorial Sloan Kettering Cancer Center (MSKCC). This enables them to handle particular situations by using computational reasoning techniques.
b. Drug Discovery and Vaccine Research:
In the drug discovery and vaccine research domain, the processes get expedited with the involvement of AI and ML. Instead of employing traditional methods, it identifies potential drug candidates or vaccine targets in a better manner. Furthermore, AI methods can also be used to identify the effectiveness and safety of chemical or biological compounds for faster development and testing processes.
c. Data Processing of Patients:
AI is highly useful in processing patients’ data, which is an important case in healthcare. A mobile app development company in Dubai can help you build healthcare apps to process enormous amounts of patient data. It helps clinicians to identify patients who are at risk of major damage or health problems.
d. Medical Imaging Analysis:
This use case of AI is still in the nascent stage, but is progressing at a great pace. With AI, healthcare providers would be able to analyze medical images, aiding in disease diagnosis and treatment. For e.g., it can identify brain tumors in MRI scans, assisting surgical planning.
By evaluating structural alterations in brain scans it can identify Alzheimer’s and dementia. Additionally, AI examines retinal scans to identify diabetic retinopathy in its early stages, which is a cause of blindness in diabetics.
e. Electronic Health Records (EHR):
AI technology is increasingly becoming indispensable in EHR management. It can analyze vast medical data to spot patterns that aid disease prevention and treatment. It can scrutinize EHR data to spot high-risk patients and suggest personalized prevention strategies.
AI forecasts the likelihood of diseases like diabetes or heart disease based on genetics, lifestyle, and medical history. In order to avoid negative drug interactions, it also highlights medication patterns and recommends substitute therapies.
f. Remote Patient Assistance:
AI allows for remote monitoring and patient assistance. Thus, the patient can get timely care with high convenience and accessibility. It also reduces healthcare costs.
Patients can share health information, get remote treatment advice, and get real-time medical help. In order to examine this data and spot trends and possible problems early, businesses in the healthcare sector use artificial intelligence. This proactive, remote strategy promotes effective healthcare delivery and lowers hospital visits.
g. Robotic Surgery:
Just like medical image analysis, the robotic surgery aspect is also in the research stage. Currently, robotic surgery is in trial for minimally invasive procedures, and sooner, they will be used for open-heart surgeries.
During preoperative planning, AI can evaluate the patients’ data and help surgeons develop more complex tactics, which further improve surgical outcomes. By prioritizing high-risk patients, controlling waiting lists, and automating operating room scheduling, machine learning algorithms also improve corporate performance.
Challenges in Implementing AI in the Healthcare App Industry:
There are many factors that have acted as catalysts for the advancement of AI in the healthcare industry. We are also witnessing the boost of Generative AI in healthcare. However, the landscape of healthcare AI isn’t without certain challenges. Let’s know about them as well.
a. Data Privacy and Security Concerns:
Healthcare is a critical industry that places high importance on data privacy and storage. When hiring mental health app developers and other healthcare app development teams, you must ensure that the developers use high-tech security methods like 2-factor authentication, data encryption, and others.
Data compliance regulations like HIPAA make it essential for healthcare institutions to safeguard sensitive patient information and implement robust security methods.
b. Interoperability and Data Integration:
In the healthcare systems, there is no consistent data format. Thus, it becomes problematic to integrate data for AI applications seamlessly. To make data integration easier, those who intend to use AI solutions in healthcare should make investments in standardized data formats and interoperable systems.
However, we can use APIs to streamline the data exchange between different healthcare systems and platforms.
c. Ethical and Regulatory Compliance:
The ethical issues include concerns about patient consent for recording data, the probability of bias in algorithms, and accountability for decision-making. For e.g., if something wrong happens due to AI results, then who will be responsible for the final outcome?
d. Limited Skilled Force:
It is not easy to find reliable mobile app developers who can integrate AI seamlessly into healthcare apps. A skilled development team must have expertise in data science, machine learning, and healthcare domain knowledge is also required.
Read More : How to Hire Mental Health App Developers?
Wrapping Up:
In this article, we have gone through all the major aspects of AI in the healthcare industry. Being a top-notch mobile app development company, we can help you develop AI-based healthcare apps from scratch. We have experienced mobile app developers with expertise in advanced features and functionalities. Let us know your requirements.
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