The use of AI in the healthcare and life sciences has revolutionized treatment monitoring, diagnosis strategies and prompted significant improvement. The technology is speeding up the pace of research into medications and helping healthcare professionals offer better and faster care. The COVID-19 outbreak has helped speed up the introduction of AI within healthcare institutions in order to maximize its benefits in a variety of domains.
AI applications are quickly becoming essential tools in everything from the diagnosis of diseases and their detection, to the efficient optimization of patient care and administration tasks. AI solutions act as virtual assistants and provide the healthcare providers and patients with unbeatable assistance. The fusion between AI and healthcare has become revolutionizing healthcare practices and generating innovative technologies for the coming years.
Although productivity is among the main benefits that are attributed to AI in a variety of industries, for the life sciences sector. But remember, it’s only the beginning of an iceberg. It has revolutionary abilities like more secure drug formulation, quicker recruiting clinical trials and the most advanced form of restorative medicine.
In this post, we will discuss how AI solutions in healthcare and life sciences can enhance patient care.
What Is AI In Healthcare?
AI in healthcare is the application of ML and natural language processing, deep learning, and various other AI technologies to improve patients’ experiences. AI predictive and data processing capabilities allow healthcare professionals to more effectively manage their resources and adopt a more flexible approach. Thanks to these advancements, doctors will be able to create rapid and accurate diagnosis, while healthcare professionals can identify electronic health records quicker and patients will receive more appropriate and timely treatment.
The incorporation of AI to the areas of biology and medicine has allowed scientists to make use of huge amounts of data to develop accurate predictions, and tackle complex medical issues. According to a report, the world AI market for life sciences was estimated at $1.3 billion in the year 2020, and is expected to grow at a CAGR of 41.2% between 2021 and 2028. This growth is due to the growing use of AI for drug discovery diagnostics, disease diagnosis, and personalized health care, which demonstrates the ability of AI to boost the research process and enhance the quality of clinical tests.
Benefits Of AI In The Field Of Healthcare
AI can bring tangible advantages for the life sciences and healthcare industry. Some of them are:
Data Analysis For Better Diagnosis
In the case of medical records, AI technology is able to process data more quickly than human beings and often more accurately. It can aid medical professionals to make a diagnosis quicker and enable doctors to complete their work better.
Better Patient Care
When properly used, AI in healthcare can increase the level of patient care provided. This is achieved by reducing research time, more efficient utilization of resources and reducing the risk of errors. Incorporating healthcare AI software into workflows can help healthcare professionals gain information when they’re making crucial choices about treatment.
Patient Care Cost Is Reduced
There are many possibilities AI could reduce the cost of healthcare, in terms of time and money. AI for healthcare could reduce the time spent on administrative duties, decrease the risk of medical errors and perform jobs much faster than human beings are in a position to.
Efficiency Of Operations
AI is able to automate administrative duties and free staff up for more valuable personal interactions. NLP can be utilized for speech-to-text functions to simplify the electronic health record (EHR) recording procedure. GenAI tools can be utilized to provide guidance and individualize in their coaching and skill growth.
Real-Time, Accurate Data
In the case of medical concerns, it’s vitally essential to diagnose the problem in the shortest time possible. In order to do that it is crucial that doctors have access to precise information that permits them to make important decisions. Real-time data reduces costs, delays, waiting times and gives a better chance of stopping the condition from getting worse.
How AI Is Transforming The Healthcare And Life Sciences Industry?
Although AI is being used in life science and healthcare, organizations have only recently begun to look into its possibilities.
Drug Discovery
The process of drug discovery is crucial as it allows the creation of new treatments and medications which can enhance and even save the lives of those with various health issues and ailments. AI based drug discovery solution can help in the identification of new drug candidates and determine their effectiveness as well as security. In comparison to conventional discovery techniques it is easier to manage, which means firms could bring medicines into the market faster and more economically.
This requires the use of AI algorithms to analyze large volumes of information to determine substances that are likely to become drugs. It could involve analyzing databases of compounds that are already in use and natural compounds, making use of AI to create new compounds.
Medical Device Design
Designing successful medical devices can be a complicated and demanding process that requires an attentive consideration of many factors including the materials used and shapes. The traditional approach required a lot of testing and error which led to a lengthy and expensive development process.
Yet, AI can help to solve these issues by improving the designs and manufacturing of medical equipment. AI can analyse voluminous data in order to determine the most efficient materials shape, sizes, and shapes that a device needs, which allows developers to make better educated choices.
Furthermore, AI can help in virtual prototypes development for medical devices. This allows designers to evaluate and improve concepts in a virtual environment thereby reducing the costs and time to create physical prototypes. Through the use of AI to improve the quality of designs of their products, businesses can speed up the development of medical devices while reducing costs and delivering better products to go to market more quickly.
Remote Patient Assistance
Telemedicine is a trend that has been inspired by AI technology, and is emerging as a major trend in the world of healthcare. With the ability to conduct remote consultations it has facilitated the availability of medical care for patients, in particular isolated settlements as well as sparsely populated areas where medical care is vital.
By using telemedicine software, physicians can give immediate advice for life-threatening illnesses improving accessibility to healthcare to a wider range of patients. A number of prominent firms are creating telemedicine software which makes use of artificial intelligence to discern symptoms and detect them which can be used to determine the diagnosis.
A few remote healthcare solutions incorporate AI and speech recognition that allows patients to inquire naturally as they would in a typical chat during an appointment with the doctor. The method ensures patients will receive timely and professional consults.
Patient Data Processing
Medical professionals are in short supply all over the world is a constant problem that predates the COVID-19 epidemic. Based on the World Health Organization, an additional 20 million top or middle-level managers are needed for medical assistance for everyone by 2030. But, the problem is likely to become more dire in the near future because of the growing global population, aging demographics, and changing health patterns.
To tackle these issues, integrating the use of artificial intelligence (AI) as well as medical knowledge databases is essential. AI is able to automate tasks such as giving out statements, filling out medical records, or answering the most basic questions of patients, which frees up time for physicians. In addition, AI can digitize and arrange vast amounts of medical records for speedy and reliable access.
By automating repetitive tasks doctors are able to concentrate on detecting serious ailments and create optimal treatments. AI will also be able to provide complete details about patients online, such as family medical histories, assisting in early diagnosis of diseases.
Pricing Drugs
Pharmaceutical companies are faced with a variety of challenges when establishing a pricing strategy. One of them is having to strike a balance between the profitability of their products with affordability for the healthcare system and patients. The area of health economics is a complex one, and pharmaceutical companies must negotiate rules regarding pricing with government agencies and payers. AI is able to predict the worth of a medicine and decide the best pricing strategy for it by looking at huge quantities of data collected from different sources, such as clinical trials, evidence from the real world and trends in the market.
ML algorithms are able to detect patterns and connections in the data, which allows pharmaceutical companies to determine the value potential of their product and the effects on the patient’s outcomes. AI is also able to simulate different pricing scenarios and anticipate the financial consequences, which allows businesses to make data-driven choices about pricing strategies. Through the use of AI, pharmaceutical companies are able to improve their pricing strategies to ensure profit with affordability while enhancing the accessibility of patients to lifesaving therapies.
Medical Imaging Analysis
The medical examinations produce a vast amount of data, which includes graphical results generated from MRI images, ultrasound scans or cardiograms and CT scans. Sorting and analyzing the images can be a lengthy and labor-intensive process for doctors. But, the introduction of AI technology is transforming this method, improving the process of analyzing visual data.
Utilizing AI-powered technology, medical specialists can benefit from the advantages of an automated method for creating medical documents and making it easier to manage their jobs. Automating the tedious process, medical professionals can direct their attention to the most important factors for serious situations, when an accurate and timely diagnosis is crucial to results for patients.
Furthermore, medical image solution assists in making more precise diagnoses by studying huge amounts of data quickly and comparably comparing the results with other studies on the identical patient. AI algorithms recognize patterns and make implicit connections that allow medical professionals to pinpoint the most important information.
Predictive Analytics
AI is able to predict a variety of aspects that influence the progression of disease and outcomes for patients. As an example, AI can help identify those who may be susceptible to developing an illness or may suffer specific complications or adverse reactions while receiving treatment. AI can also help predict the success of particular treatments specific to patients depending on variables such as their background medical history, their genetics and their lifestyle.
In addition, AI can help forecast the progression of disease over time that can help inform the treatment plan and enable quicker intervention in some instances. AI can improve healthcare outcomes by making more precise medical decisions that are based on specific information about patients.
Simplify The Tedious Administrative Processes
AI changes the conventional approach of handling patient information. Through the integration of AI tools healthcare software development, administrators will be able to easily correct mistakes and create accurate reports. Additionally, AI-powered software handles every aspect of data from patient appointments to billing, allowing health professionals to concentrate on activities that add value and offer the highest-quality treatment to their patients.
Fraud Detection
Drug fraud is a result of prescriptions that may result in severe negative health outcomes for patients taking the medication in the absence of medical supervision. This could contribute to the bigger problem of abuse and dependence. AI could help in preventing this from happening by utilizing machine learning algorithms that detect certain patterns or anomalies within prescription records like excessive amounts or doses of specific drugs from healthcare professionals.
AI-powered systems can examine prescription records in conjunction with different data sources like the criminal record and insurance claim data, in order to detect the possibility of abuse or fraud. By detecting and stopping the fraud, AI can help promote patient security and decrease the negative impact of drug misuse on society.
Step-By-Step AI In Healthcare Software Development Process
In this section, we will discuss the steps to develop smart AI healthcare software solutions that promote the development of new technologies and increase efficiency.
In-Depth Research and Competitor Analysis
Prior to collaborating with any AI software company make sure you are aware of the goals you want to achieve. Once you have established your goals, effectively invest in AI powered healthcare software development. When the necessity for developing healthcare AI software is determined, you must study the subject thoroughly. Choose an experienced AI development company to assist you. Always study your competitors’ offerings to determine what AI-powered methods they are using.
Look For a Reliable AI Development Company
Locating the most suitable healthcare software development firm to work on your venture is the crucial step towards developing the AI healthcare software. If you opt for an internal group, you’ll find yourself in the stressful method of interviewing and educating the full-time developer that will fulfill your demands.
The budget is likely to be raised as well as the timeframe to finish the AI healthcare software development can be extended. So, employing dedicated software development experts from a well-known AI software development company is a better option.
Algorithm Development and Training Models
The healthcare software development team will choose algorithms based on the information available as well as the complexity of the task. The team you choose to work with will make use of common algorithms, such as convolutional neural networks (CNNs) and Support Vector Machines (SVMs).
The next step is to create ML or deep-learning models following the selection of an algorithm. The model’s architectural structure has to be created, the application design firm should select the appropriate layers as well as connections. They have to specify the input and output structures.
The algorithms used for the AI healthcare software must be developed using a large amount of health-related data. This data could include information about the patient’s demographics, electronic health records and additional pertinent information.
Testing and Deployment
Your company that develops healthcare software is going to complete the integration in order for seamless data exchange between AI-driven applications and your health technology. When the software is integrated and tested, you must thoroughly check the AI software to make sure that it is working without glitches. AI software development specialists offer automated and manual test methods to show the software reliability. After testing is completed they will deploy the solution.
Challenges Associated With AI Implementation In Healthcare
Although AI will certainly revolutionize the healthcare industry however, it also poses certain challenges, like:
Data Privacy
One of the most significant worries about the usage of AI in the field of healthcare and life sciences is getting access to personal information of users or patients. Health records, medical records, and other information are classified as sensitive personal information, which is why they are protected by a higher level of security.
AI and ML technology works effectively upon large sets of data; the lack of access to data can make it challenging to design effective tools that allow to make accurate diagnoses. Yet, keeping private personal data safe is the biggest challenge faced by organizations that use the same data to develop AI algorithms. Furthermore, privacy law imposes a strict obligation for those who handle such sensitive information.
Training Resources For AI Implementation
A further issue that is associated with the application of AI in the field of healthcare is the inability to provide technological training for the individuals involved. Healthcare professionals should be well aware of the ways in which AI technology can be utilized for specific healthcare units. But, AI technology can be complicated to grasp. This makes it challenging to offer individualized education to a variety of sources.
Uncertainties About The AI Algorithm
AI certainly has made a major impact on the field of healthcare by being able to detect ailments at an earlier phase. But, there’s some doubt regarding the efficacy that is being offered by AI technology. It has created a sense of doubt regarding the use of AI within standard healthcare processes.
Lack Of Implementation Framework
There is a wealth of research on the ways AI will transform the healthcare industry, there’s no research that focuses regarding how to apply AI in the field of healthcare and life sciences. This has resulted in a gap among healthcare executives as well as practitioners and patients as a majority of individuals aren’t aware of the ways in which AI is able to integrate with existing procedures. To address this issue, it is necessary to establish an adequate framework in place to allow healthcare executives to implement AI into the field of healthcare.
Ethical Challenges
Accountability plays an essential aspect in the medical field. Since AI technology learns to train itself using the information given, we are unable to ensure the way it provides outcomes. If a wrong diagnosis leads to a traumatic incident, it’s hard to determine the level of the responsibility. In addition, the lack of any standard ethics guidance makes it challenging to establish responsibility.
Real-Life Examples Of Ai In Healthcare
Artificial Intelligence isn’t something new in the field of healthcare and life sciences. Companies have already incorporated the most effective AI solutions to increase the efficiency of their operations, productivity and revenue. Here are a few top examples of this:
GE Healthcare
Intel along with GE Healthcare have developed a revolutionary AI algorithm that integrates in X-ray equipment to improve the patient’s care. This collaboration has improved AI for medical imaging. Utilizing Intel Vision technology and the OpenVINO toolkit, the new technology referred to as GE Health’s Critical Care Suite, improves the efficiency of AI algorithms, and reduces the time needed for examining X-rays from greater than 3 seconds down to under one second.
Trial Pathfinder
Trial Pathfinder is an open-sourced AI framework that was developed by a small group of scientists from Stanford University. It allows organizations in life sciences to gain access to real-world data i.e. and patient health records, and utilize it to create simulations of clinical trials. Researchers can utilize Trial Pathfinder to evaluate drug efficiency and survival rates.
Atomwise
Atomwise is a preclinical pharmaceutical research organization that uses AI to help speed up the process of drug discovery. AtomNet is a neural network-based technology that they invented that has enabled them to find more “undruggable targets” than any other pharmaceutical discovery platform made possible by AI.
The company works with more than 250 organizations in the field of life sciences around the world, helping to develop innovative solutions for more than 600 ailments. This includes neurological, cancer, cardiological disorders, and infections. The ultimate goal of the company is to develop a new pharmaceutical discovery process.
In Summary
Artificial intelligence (AI) has revolutionized healthcare and life sciences sector, offering multiple benefits to doctors and patients. It would be right to say that AI is developing quickly. Healthcare institutions already have the foundational information strategies that are a vital element in the initial phase of adopting AI technology.
AI in healthcare has helped enhance the way that healthcare professionals operate. A rapid adoption process is underway, as organizations and patients they care for are beginning to reap the advantages. As AI revolutionizes the healthcare and life sciences industries new challenges arise, which include the requirement for high-quality data, ethics, as well as regulation supervision. Experts in data analysis are essential to ensure that AI models are trained correctly which is why it’s crucial to solving the challenges to realize the potential of AI in the field of healthcare and life sciences.
