Artificial Intelligence in Healthcare and Medicine

The healthcare industry is adopting impactful technologies for improving patient care. Artificial intelligence (AI) in medicine and healthcare is a hot topic for the past few years. It is becoming a revolutionary technology in healthcare in this digital era.

AI in healthcare takes over all routine tasks of physicians, administrators, and even patients. AI-powered tools reduce the cost of service and offer high-level treatments in very less time. This was the core pillar for the increased deployment of AI in healthcare.

AI-driven tools and apps benefit providers from radiology to identifying tumors. Artificial Intelligence applications in healthcare find new ways to develop new drugs. It was one of the significant benefits of AI in the healthcare industry.

In particular, various types of cancers are increasing the death count of the population. Something has to do in the healthcare sector to overcome this challenge. AI uses machine learning and deep learning technologies to find new patterns in existing medicine, and thus it helps drug development companies to discover new drugs.

Besides, from medical imaging and risk analysis to diagnosing health conditions, AI augments every task. Accordingly, the use of AI in developing healthcare robots is also helping doctors in multiple ways.

The best news is AI technology is efficient in detecting dangerous COVID-19. AI-powered rapid screening systems can find unique features of the COVID-19 virus even the patients come across normal CT scans. It is one of the best and most useful advantages of AI technology in healthcare.

Not only these benefits but, Artificial Intelligence in the medical field has wide growth opportunities. Of course, growth opportunities will not come without investing, but your investment should not drain. I mean to say, invest in emerging technologies to get increased return on investment.

With 20+ years of experience in providing AI solutions, USM believes that investment in emerging technologies like artificial intelligence, machine learning, and other future technologies will always give profitable financial boundaries in this digital world.

Now, we’ll discuss a few significant use cases of AI in healthcare.

Significant Benefits Of Artificial Intelligence In Healthcare

Generally, the applications of AI in healthcare are categorized into three groups. Such as patient-oriented, clinician-oriented, and admin-oriented. The future of AI in healthcare and medicine will fall into these groups. Here is the list of major use cases of AI in healthcare (future of machine learning in healthcare).

Let’s take a look at How AI is transforming the future of healthcare?

#1. AI Helps To Reduce Manual Errors and Improve Diagnostic Processes

The most exciting artificial intelligence healthcare applications help doctors to improve diagnostic procedures. AI in medicine is useful for automating the diagnosis process and the ways patients get their treatment.

Today’s healthcare industry, specifically in developed markets like the USA, is highly using AI for accurately predicting patients’ diseases faster than medical professionals do.

Accordingly, AI is also used for maintaining electronic healthcare records more efficiently. Intelligent machines perform more accurate functions than humans and mitigate the error rate.

Below is the list of a few healthcare companies that use artificial intelligence to provide faster medical operations. Let’s have a look at it!

• PathAI

Location: Austin, Texas and Boston, Massachusetts
PathAI delivers an AI-powered pathology solution using Machine Learning (ML) and deep learning algorithms to assist pathologists in fast diagnosing and providing treatment for today’s challenging diseases.

• Buoy Health

Location: Boston, Massachusetts
Buoy Health has developed an AI-powered health assistant. Buoy’s AI assistant can listen to your symptoms and guide you to take the proper treatment based on its diagnosis.

• Enlitic, Inc.

Location: San Francisco, California

It is striving to build a bridge between humans and emerging AI technology to advance the medical diagnosis process. Enlitic’s AI tools improve the quality and efficiency of medical imaging to diagnose and treat diseases.

The company’s Artificial intelligence tools using deep learning algorithms examine unstructured medical data like X-ray images and blood sample reports. This process would assist doctors to improve the outcomes of patients.

• Freenome

Location: San Francisco, California
The company is specialized in using Artificial Intelligence technology in diagnostic and blood tests to quickly identify and treat life-threatening cancer in its earliest stages.

These are just a few companies that are using AI in healthcare. The leading research companies and biotech companies are using AI for improving diagnostic processes and reducing errors in detecting disease.

#2. Artificial Intelligence In Developing New Medicines

The future of artificial intelligence in healthcare for drug development has higher scope than other applications. The potential for artificial intelligence in healthcare for the design and development of new medicines to treat various types of life-threatening disorders

The drug development industry needs more money and time in developing and introducing new drugs into the market. Research, design, development, clinical trials, and patent approvals are all time and money-consuming processes. It costs billions of money to bring a drug through clinical trials.

To improve drug efficiency and reduce development costs, pharmaceutical companies are using AI technology in their operations.

Atomwise: (Location: San Francisco, California)

Atomwise is the best instance that uses Artificial intelligence for drug development. The company is using AI technology to discover new medicines that help to treat Ebola and multiple sclerosis. Atomwise’s AI platform for healthcare can screen millions of genetic compounds and deliver results faster than traditional drug development enterprises.

#3. AI To Improve Patient Experience

Are you a healthcare service provider? Are you providing a great experience to your patients?

If not, start now. Because when you provide a great experience to patients, you can achieve brand loyalty. Lack of proper service declines your brand in the market.

Artificial intelligence technology helps hospitals, doctors, as well as clinics to better serve their patients. Have a brief discussion on how AI is helping healthcare service providers to enhance patients’ experience.

• Qventus, Inc

Location: Mountain View, California
Qventus is the best AI-powered software that helps patients in overcoming operational challenges in the hospital. From OPs and surgery to emergency care units, Qventus software efficiently manages the flow of in-patients and outpatients. Thus, this AI-powered healthcare solution boosts decisions in hospitals to improve service quality and experience.

• CloudMedX

Location: San Francisco, California
CloudMedX’s AI platform uses ML algorithms to continuously track and manage the patient journey across the healthcare system. It helps hospitals better manage their patient’s data including date of admission, medical information, and also payment data. So, healthcare providers using these data can easily deal with patients when they are discharged without any confusion.

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Like these, healthcare companies can benefit from this kind of artificial intelligence application to improve patient experience in real time.

#4. Artificial Intelligence To Manage Medical Information

It is one of the significant benefits of artificial intelligence in healthcare. The healthcare sector is one of the targeted industries for hackers. The industry is highly prone to information (medical records) attacks. Hackers will always try to hack the healthcare records to sell in the black market and earn profits. So, to efficiently manage medical data, particularly the data used for discovering new drugs and providing better diagnoses, Artificial intelligence makes sense here.

AI in medical field gives tremendous benefits. This is one of them. AI technology helps to segment the vast medical database and make the data process seamless.

Below are a few AI companies that deliver innovative AI solutions to manage their vast medical data better. Let’s start.

• Tempus

Location: Chicago, Illinois
Tempus’s AI-powered tools are engaged in collecting and processing vast clinical and molecular data of patients. This analysis helps doctors to provide personalized health treatments to their patients. The company is also using AI technology to continue its research and development function for cancer treatments.

• KenSci

Location: Seattle, Washington
Using big data and AI, KenSci’s intelligent solutions help to prevent future health risks. The company’s risk prediction platform helps healthcare organizations detect clinical and financial risks by grouping diverse data from existing sources. The sources include electronic medical record systems, ADT (Admissions, Discharges, and Transfers), ), and financial data.
This risk prediction system can easily identify who is at risk and who needs medical attention immediately. Thanks to artificial intelligence!

• H2O.AI

Location: Mountain View, California

Artificial intelligence is rapidly transforming healthcare. H2O.AI is one of the best AI companies specializing in delivering AI solutions. H2O.AI’s artificial intelligence platform offers improved clinical workflows, analyzes patient risk, and predicts ICU transfers. Using this solution, hospitals can ultimately achieve positive medical outcomes.

Thus, managing medical data not only helps to automate the process of collecting, storing, and processing patient information, but also assists hospitals in enhancing their entire healthcare system by providing personalized treatments.

#5. AI Robot-Assisted Surgery

In the recent past, the healthcare industry is observing a skyrocketing growth in performing robot-assisted surgical functions. Robot-assisted surgeries offer less pain and quick recovery time. Thus, AI robots optimize the process of surgery and reduce errors that may happen with physicians. Below are the best and a few examples of AI companies that develop surgical robots.

• Auris Health (Redwood City, California)
• Accuray (Sunnyvale, California)
• Intuitive (San Francisco, California)

#6. AI for developing efficient radiology tools

Artificial intelligence in the medical field brings advanced radiology tools to the market. They can accurately diagnose diseases and provide instant insights to physicians on patient data.

#7. AI Brings intelligence to medical devices

The future of artificial intelligence in healthcare for developing intelligent and virtually supporting medical devices is bright and has a greater scope. Using neural networks, deep learning, and predictive analytics, artificial intelligence in medical devices will help physicians identify disease types and predict their severity.

Further, AI in the medical field is best useful for developing smart devices and machines. Smart devices will monitor patients’ conditions and notify physicians are any complications they found. Such AI devices reduce costs and ensure 24*7 in-patient care.

#8. AI wearables for monitoring health

From step trackers to smart bands, AI helps in collecting valuable data on users’ health. Heartbeat, blood pressure, oxygen levels, steps walked, and sleep quality everything will be tracked and analyzed with AI. Such innovative AI-enabled wearables are extremely useful for elders in tracking their health.

These are the top 8 ways artificial intelligence will impact healthcare. The future of artificial intelligence in healthcare will be around these AI use cases in healthcare and medicine. The ultimate aim of all these applications of AI in healthcare is-

• Improving clinician productivity
• Enhancing patients’ engagement &
• Accelerating the speed of treatment

Conclusion

The future of AI in healthcare and medicine is promising and will offer unlimited growth opportunities for healthcare service providers. From digitizing doctor consultations, automatic records maintenance, and virtual access to patients’ health conditions to minimally invasive robotic surgery and telemedicine services, the benefits of artificial intelligence in healthcare are unlimited. AI technology plays a significant role in accelerating digital workflows across care services.

USM is the best AI healthcare app development company in the USA. We offer design, development, deployment, and maintenance of AI apps and solutions for the healthcare sector.

Explore more about USM’s AI-driven healthcare solutions and services. Talk to our AI expert and get your product now!

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Machine Learning (ML) is a significant application of Artificial Intelligence. As we discussed in our ML blog category, applications of machine learning in healthcare learn from previous experiences or data, identifies patterns, and forecast future events.

These predictions add value to businesses. This was the major reason behind the increased demand for ML techniques. Several industries are using ML in their multiple applications for various purposes.

It’s a globally known fact that the digital world is making data accessible in a simple way. The vast amount of data is collecting, storing, and processing easily using intelligent technologies. On top of this, increasing the computing efficiency of innovative technologies made data profitable for businesses.

In addition, processing toolkits, open-source frameworks, and immense libraries are all available at affordable prices, and thus, building and executing ML applications is growing worldwide.

Though ML is giving lucrative benefits to industries, its impact in the healthcare industry is unbelievable. Machine learning in healthcare leads to some thrilling developments in oncology. Diagnosis of cancer and providing accurate treatment at the right time will become more feasible in the coming years with ML.

Machine learning algorithms the sensitivity-level of diagnosis, and helps physicians to make the right decisions to provide value-added treatments. Therefore, ML-based machines assist healthcare service providers to offer personalized treatment experience to their patients.

Yes, this reinforcement learning can also improve employee productivity in hospitals. Of course, the applications and uses of ML in the healthcare sector are infinite. In this blog, we briefed a few major uses cases of Machine learning algorithms in healthcare. Let’s start!

#1 Disease Detection

Healthcare machines are overloaded with increasing usage. This was primarily due to a growing population and with the same proportion of increasing diseases. The machines are continuously working to identify the diseases of the patients.

However, traditional machines are not capable of doing this efficiently. But, machine learning models can detect diseases with more accuracy at less time. It’s a proven fact!

Researchers have been still working on exploring machine learning in the healthcare sector. They are continuing their innovation in developing more efficient models of machine learning. Currently, machine learning methods help doctors in the early detection of diseases before the disease reaches to severe level.

The global leading technology companies are developing neural network artificial intelligence systems for accurate detection of difficult respiratory disorders. These machines, in connection with the IoT-based sensors, can precisely analyze respiratory problems and avoid risks and hospitalizations.

Nowadays, new deep learning-based disease prediction methods efficiently identify cancer in early stages. These models are trained with the patient’s medical records to detect irregular patterns that cannot be observed by human physicians.

#2 Robotic Surgery

Today’s intelligent robots are completely altering the way of doing surgery. They are designed to perform complex surgical functions. Robots can also reduce the time of surgery.

Robots can perform cardiac, spine, orthopedic hip and knee replacement, neurology, cancerous tumor irradiation, and other significant surgeries. Robotic surgery is minimum invasive and offers 99.9% positive patient outcomes.

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AI and ML-based surgical tools can enhance the processing of medical records. Also, they can give self-reviews based on past surgical experience. Therefore, the use of robots optimizes the process of surgery and reduced errors that are may happen with physicians.

#3 Personalized Medicines

The current technology is restricted doctors to estimate the risk level of disease based on the patient’s previous medical history and genes. Using AI & ML, the researchers are finding new ways of developing further matured personalized medicine for various diseases.

Machine learning in medicine is shaking today’s healthcare sector. ML-machines can provide numerous treatment ways when they trained with the patients’ medical records. In the next coming years, we will surely observe the manifold of intelligent devices and sensors with infinite capabilities.

#4 Smart Health Records

The manual process of keeping healthcare records up-to-date is a bit complex procedure. Though technology is playing a significant part in enabling data set entry procedures, still, the process was very lazy and taking too much time to enter the training data.

Here, unsupervised learning comes into place. The major role of machine learning in healthcare is to make every process simple, complete the task in a very short span.

So, ML-based smart health records avoid manual errors and automatically update the patient’s health data. Thus, the updated learning from data is very much useful for doctors to provide treatment/medical suggestions to the patients.

#5 Research and Clinical Trials

Machine learning has been widely using in medical research and clinical trials. Clinical trials of new drugs are cost-efficient, and take years to complete and get approvals from authorities.

Many pharmacy companies are now using ML-based predictive analytics for identifying latent clinical trial candidates. Machine learning models prefer electronic records to avoid unlabeled data-related errors.

#6 Improved Radiotherapy

One of the major use cases of machine learning in healthcare is in the radiology field. ML-driven algorithms can automatically learn from massive various samples to detect the patterns.

Using machine learning, the radiologist can easily categorize regular or irregular impressions in a medical image. This scenario helps to diagnose the disease level and provide proper treatment at the right time.

#7 Disease Predictions

The power of AI and ML technologies in healthcare is incredible. The government and private healthcare service providers are deploying AI & ML-based systems for many purposes.

Among other, ML and predictive analytics benefit healthcare providers to accurately predict a wide range of diseases from malaria to chronic and infectious diseases. This capability of ML helps for those markets that have no proper medical infrastructure for identifying such kind of diseases.

#8 Drug Discovery and Manufacturing

Drug discovery was a major clinical use case of machine learning. Next-generation sequencing and precision medicine technologies are also widely using in detecting multiple ways to provide therapies for various diseases.
The use of ML in drug discovery will help to reduce the cost of introducing new drugs to the market, and also make the drug discovery process faster.

#9 Crowdsourced Data Collection

Nowadays, crowd sourcing in the medical industries is all the rage, enabling practitioners and researchers to obtain high amounts of the data uploaded by individuals depending on their own consent. There are tremendous changes in the way medicine is perceived in these live health data.

Tech giant, IBM has recently associated with Medtronic to decipher, accumulate, and make available insulin and diabetes data depending on the crowd sourced information.

As progress is made in the Internet of Things (IoT), the healthcare sector is finding new ways to use this data and to address tough-diagnosis cases and the comprehensive development of diagnostics and drugs.

#10 Machine Learning-based Behavioral Modification

Behavioral modification is a significant part of preventive medication, and since machine learning usage has expanded in the healthcare industry, a large number of startups have been growing in areas such as cancer recognition and prevention, patient diagnosis and treatment, and more.

Somatics is a B2B2C based data analytics firm that has released an ML-based applications to identify gestures we make in our day to day lives, which allow us to understand our unconscious behavior and make necessary changes.

Wrapping Up

USM Business Systems has vast experience and best practices in using AI and its technologies, deliver high-level AI and ML solutions and mobile apps. We have achieved excellence in AI and ML, but further developments in intelligent technologies are needed in this society.

Our machine learning services for healthcare have helped many clients to save their time and costs. Our Machine learning solutions enabled our customers in uplifting their offerings for this modern world.

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