How to Use AI and Mobile Apps for Personalized Medicine: A New Frontier in Healthcare

Cancer and other terminal diseases have been the enemy of humankind since the beginning. A report by the World Health Organization estimated 20 million new cancer cases in 2022 with 9.7 million deaths. WHO promotes early detection and diagnoses to reduce these cases. With advanced technology at our disposal, the healthcare sector is getting the right assistance in better patient care and early detection. 

Artificial Intelligence is at the forefront of this new revolution where tech resources are influencing the healthcare sector. AI-driven Healthcare mobile app development is being embraced by major healthcare institutions to serve their patients with personalized treatments. AI has the capacity to analyze the vast amount of clinical documentation to identify disease markers that are often ignored. 

We put on our research hats and went to work scouring numerous resources to create this article. Here’s how Healthcare companies and institutions are using Health care mobile apps for personalized medicine and timely patient assistance. 

Using AI for better healthcare 

Artificial Intelligence is growing fast. Twenty years ago, no one would have thought chatbots could manage customer support. Video calls with doctors and virtual reality home tours also seemed impossible. Today, AI is changing many industries, especially healthcare, by making things easier and more efficient. Many of these improvements come from combining AI with mobile apps and patient management systems. Here are some of the top ways AI helps with healthcare:

• Create individual treatment plans based on the patient history and condition.
• Easy access to electronic records of patients.
• Home monitoring of patients with critical conditions.
• Automated patient appointments and report delivery.
• Accurate detection of diseases.

Types of AI technologies in healthcare

Artificial Intelligence is a broad field, and its subsets play a key role in shaping the healthcare industry. The different components of AI help healthcare practitioners with various tasks. From managing patient records to delivering personalized treatment, they function at different stages. Let us examine some of the different technologies associated with AI and their benefits:

1. Machine Learning

ML technology studies huge data sets and documents to identify patterns. This information predicts diseases and their possible cures with great accuracy. The power of data analysis also helps in analyzing patient records and medical imaging for quick diagnosis. Patient-specific data assists in creating customized and personalized treatments for patients with varying medical conditions. Using and studying data with ML algorithms speeds up the medical treatment and diagnosis process, which is not possible using traditional methods.

2. Natural Language Processing

NLP does interesting work. It allows computers and systems to analyze human mind and behavior and imitate it, often with better precision. Through medical record analysis, NLP systems provide physicians with precise illness identification capabilities and essential insights drawn from advanced health data. NLP helps healthcare professionals discover the correct treatments and medications for each patient to improve their personalized medical care.    

NLP brings groundbreaking value to healthcare through past medical history assessments which help providers intervene before risks become problems. Healthcare operators use powerful tools from NLP to deal with sophisticated clinical datasets which would otherwise need many hours or entire days to process manually.  

3. Supervised Learning Models

Medical professionals use supervised learning models to study datasets with established inputs and results that facilitate early disease recognition. SLMs identify correlations between disease symptoms and biomarkers which lead to precise estimates of future condition occurrence. The combination of patient data with laboratory results and medical images enables systems to detect early warning indicators for conditions including cancer and heart disease. 

These models become increasingly accurate by using new datasets to perform ongoing training processes. The collected insights enable healthcare professionals to execute timely interventions while enhancing treatment plans which produce superior patient outcomes for a new age of preventive healthcare.

Benefits of using AI mobile apps in healthcare and patient care

The advantages of AI mobile apps in healthcare are diverse and impactful. They take the industry towards a significant development, which benefits patients and healthcare experts alike. Have a look at a more detailed explanation below:

✔️ Personalized treatment for patients

Every patient is unique, which means they visit doctors with varying medical conditions and symptoms. For example, two patients with high cholesterol may experience different symptoms and require personalized treatment approaches. This is where AI-powered mobile apps assist medical professionals in developing customized treatment plans. By storing and analyzing patient data, these apps help doctors identify the most effective treatment options tailored to each individual’s needs.

✔️ Fast medical research analysis

With the help of ML algorithms, experts get access to the latest research papers. Doctors can instantly search this repository to find reliable information on a specific condition. The mobile app is designed to help healthcare experts in analyzing these long and complicated medical research papers. They often provide a summary, allowing the experts to make decisions accordingly and find what they were looking for.

✔️ Improved patient management

Managing the information of countless patients is a time-consuming task, especially when it is done without proper tools. But a mobile app integrated with the Electronic Health Records eases this task. Health experts can look up the patient in these records and find every minute detail about them. From their previous illnesses to the recent health reports, everything is available at your fingertips. This makes patient management a more refined process, identifying overlaps and improving patient care. These apps smoothen the clinical workflow and reduce the overall spending at healthcare facilities.

✔️ Accurate medical imaging

Today's medical services heavily rely on imaging technology for diagnostics and pathology, yet exclusive expertise and experience remain necessary to interpret these images effectively. The field of medical imaging analysis has, in recent years, experienced a major transformation shift with AI automation which now provides better screening and risk management, and precise medical treatments.  

● Research published on the National Library of Medicine explains how computational tools are often used to aid detection of COVID-19 from lung ultrasound images.

● Automated system from the study showed how it enables emergency room physicians to analyze lung ultrasound images for COVID-19 diagnosis assistance.  

Artificial intelligence detection systems show potential to identify medical conditions such as heart failure through on-site point-of-care assessments.  During urgent times like the pandemic's initial emergency phase, concerned departments found this technology essential for providing valuable help with patient care. Scientists are researching how to add these tools into wearable devices and wireless technologies to enhance remote patient healthcare services.  

Using AI and mobile apps for personalized medicine

Personalization is a popular trend, particularly in most business sectors, including healthcare. A survey by Boston and Consulting Group found that institutions investing in personalization witnessed a 10% improvement in customer experience and a 5-10% reduction in administrative costs.

The report also states that people prefer to take charge of their own health, and the personalized experience fits well with their preferences. They get the treatment that not only solves their health issues but also gives them a psychological assurance that the particular treatment is ‘unique’ to them. 

Personalized healthcare delivers three main types of values:

1️⃣ Patient satisfaction

According to Harvard Health, there is a fine link between good mental and physical health. The same idea applies when patients receive personalized care based on their preferences. They feel reassured knowing their treatment plan is tailored to their medical history and condition, making it the best course of action for them. This often leads to higher patient satisfaction, a stronger desire to recover, and a greater sense of hope. With the help of an AI-powered healthcare app, personalized treatment plans can be created instantly.

2️⃣ Greater healthcare value

The customization of healthcare services through personalization improves health results by creating specialized treatments which consider patients' individual requirements and clinical background. The combination of AI technologies together with data analytics allows healthcare providers to develop exact diagnoses and predict medical risks while creating tailored medical approaches. The healthcare value increases alongside a patient’s happiness when providers leverage this approach which leads to predictive care and better experiences for everyone.

3️⃣ Revenue growth

Health institutions providing personalized patient care see a spike in the revenue growth. Satisfied patients have more chances of returning to your facility in the future, turning into permanent customers. You also get better Medicare ratings by making your patients feel valued and heard. Personalization also includes membership programs for customer retention.

Other uses of AI in the healthcare sector

Apart from the benefits mentioned above, healthcare clinics have determined various other uses of AI. 

➔ Drug Discovery

This technology has helped identify new treatment options for various health conditions. However, high drug development costs remain a major challenge for pharmaceutical companies and research teams. Many newly developed drugs fail to receive FDA approval, resulting in significant financial losses. AI and machine learning help overcome this hurdle by using advanced algorithms to analyze drug development processes, identifying potential issues and faulty patterns that human researchers might overlook.

➔ Genomics

Genomics play an exciting role in personalized medicine. This is done by analyzing large and complex datasets that only AI and ML algorithms can study. Big data analytics and AI models can tailor care and treatment recommendations for various medical conditions. Accessing a patient’s genetic information is a time taking process when done manually. But AI accelerates this process, identifying potential health concerns like hereditary and genetic diseases.

➔ Revenue Cycle Management

Traditional medical revenue cycle management relies on manual processes, which are time-consuming and place a heavy burden on organizational resources. With advancements in AI, more healthcare organizations are adopting automation to improve efficiency. Providers are now leveraging AI tools to streamline claims management, reducing the effort needed for denial resolutions and medical coding, enhancing workflow efficiency.

Efficiency enhancements in healthcare now hinge on three key technological systems which include:

• Autonomous coding 
• Patient estimate automation 
• Prior authorization tools

Healthcare organizations are strategically investing in automation to enhance operational efficiency. Their primary goals include minimizing manual tasks, safeguarding patient data, and providing accurate cost estimates for various medical expenses.

Case studies of using AI in healthcare

Google Health

AI for Dermatologists: Google is leveraging AI and image search technology to develop a dermatology-focused tool. This tool is designed to help individuals assess their skin, hair, and nails for potential conditions. It covers more than 80% of clinical conditions and over 90% of commonly searched concerns. With this technology, users can easily identify minor conditions, enabling early detection and informed decision-making.

Detecting early signs of anemia from the eye: Research by Nature Biomedical Engineering revealed deep learning algorithms identify anemia in 1.6 billion individuals across the world through the analysis of de-identified eye fundus pictures. Higher diagnostic accuracy through non-invasive testing of the eye's back side provides a potential path for early anemia detection which might lead to better treatment.

Also Read: How AI and Mobile Apps Are Transforming the Driving Experience for Smart Cars

Choose SkyTech Mobile for an all-in-one healthcare mobile app 

Healthcare facility owners looking to enhance patient care through personalized treatment can achieve this by investing in healthcare mobile app development. As highlighted in this discussion, the healthcare industry is rapidly evolving with advanced technologies like AI, enabling more tailored and efficient services.

If you are searching for a top-tier mobile app development company, SkyTech Mobile is your go-to-market solution. As a division of Sofvue LLC, we bring together a highly skilled team, extensive resources, and deep technical expertise in AI and LLM development to build innovative, results-driven healthcare solutions.

Our certified mobile app developers specialize in creating intuitive and customized applications that align with your facility’s needs. Contact our support team today and take the first step toward transforming patient care with innovative technology.

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Citations: 

1.World Health Organization: https://www.who.int/news/item/01-02-2024-global-cancer-burden-growing--amidst-mounting-need-for-services

2.World Health Organization:  https://www.who.int/activities/promoting-cancer-early-diagnosis

3.Boston and Consulting Group: https://www.bcg.com/publications/2022/how-to-develop-healthcare-personalization-capabilities

4.National Library of Medicine:  https://pmc.ncbi.nlm.nih.gov/articles/PMC10928066/

5.Harvard Health: https://www.health.harvard.edu/topics/mind-and-mood#:~:text=There's%20a%20strong%20link%20between,disease%2C%20and%20other%20health%20issues.

Google Health: https://health.google/health-research/imaging-and-diagnostics/