How to Benefit from AI In the Healthcare & Medical Industry

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Artificial intelligence (AI) has the potential to vastly improve healthcare around the world. The primary reason is that currently, patients often do not receive medical care in a timely manner. Symptoms of disease may be misdiagnosed, or individuals may require bespoke treatment that accounts for their medical history. Medical personnel may be swamped with work and unable to give patients their full attention. How patients take care of their own health is also a “black box”, since doctors have no control over their behavior after consultation. As the populations of developed nations grow older, it is imperative that AI-empowered technologies like machine learning (ML) and computer vision are used to advance the quality of healthcare services.

Resources:
What is Artificial Intelligence (AI)?
What is Machine Learning (ML)?
What is Computer Vision?

AI may be utilized in the medical industry in numerous ways. For the sake of simplicity, we can use the umbrella terms “diagnosis” and “treatment” to separate them into two categories.

Diagnosis is about detecting the signs of illnesses as quickly as possible. For this, physicians need AI tools that can help them make the right call, as well as conveniences that let them devote more time to their patients. Treatment is about how patients are cured and cared for. AI-enhanced personalized medicine can heal ailments more effectively, while remote monitoring and telehealth services can aid patients during the recovery process. Last but not least, drug development can be made faster, safer, and more precise with artificial intelligence and high-performance computing (HPC).

As we approach the period in human history when AI will be able to take care of our wellbeing, it is important to understand that the global healthcare AI market is still in its nascent stage. Exciting new breakthroughs may change our views on what it means to go to the doctor, but rules and regulations will also have to be put in place to protect our safety and privacy. It goes without saying that the use of patient data must be within the boundaries of the law and restrictions on patient privacy. Innovative services must abide by all legal, professional, and ethical compliance standards, as set by the relevant authorities.

In the following sections, we will explore AI applications for diagnosis and treatment. What’s more, we will introduce the server hardware and software solutions that can help you benefit from this worldwide trend.

Resources:
What is High-Performance Computing (HPC)?
What is Server?

Healthcare analytics refers to the examination of historical medical data to pinpoint the common indicators of disease. Not only will this help physicians diagnose sicknesses with greater accuracy and efficiency, it’s also a good way to glean value from old medical records. Since most of the data is gathered through medical imaging—e.g., computed tomography (CT) scans, X-rays, ultrasounds, and magnetic resonance imaging (MRI)—teaching the AI to work with medical images will give healthcare analytics a shot in the arm.

Typically, the AI is trained with input that comprises an enormous library of labeled medical images, with parameters numbering in the billions, or even trillions. Through a process known as deep learning, the AI model makes “guesses” about what it’s seeing, and then it checks its answers. Over time, the “weighted scores” that the model assigns to the data parameters become so precise, it will make the correct guess every time. In other words, it’s learned to recognize the symptoms of diseases in medical images.

Because the AI is trained on an enormous dataset, and because a lot of the data is in graphical form, servers that can engage in parallel computing by using the latest graphics processing units (GPUs) are recommended for injecting AI into healthcare analytics. GIGABYTE Technology’s G-Series GPU Servers give you access to a wide range of advanced GPU products. For example, the NVIDIA-certified G593-SD0 GPU Server integrates the HGX™ H100 8-GPU computing module to create one of the most powerful AI training platforms on the market. Another exciting option is the “CPU plus GPU” package that’s specifically designed for AI and HPC workloads. Your options include AMD Instinct™ MI300A, which is AMD’s enterprise-grade APU (accelerated processing unit) product, and the NVIDIA Grace Hopper™ Superchip, which is available on GIGABYTE’s H223-V10 and H263-V11 H-Series High Density Servers.

In addition to the state-of-the-art hardware, GIGABYTE’s investee company MyelinTek Inc. offers the MLSteam DNN Training System, which is an “MLOps Platform” that integrates popular deep learning frameworks for medical AI development, like NVIDIA MONAI, with beneficial tools handpicked by MyelinTek based on its extensive experience working with doctors and other healthcare service developers, like labeling tools and image programs. Working with GIGABYTE and MyelinTek can help you set up your AI-infused total solution in record time.

Resources:
What is AI Training?
What is Deep Learning?
What is Parallel Computing?
What is Graphics Processing Unit (GPU)?
What is OCP?
What is MLOps?

The benefit of AI-assisted consultation is that physicians can use pre-trained models to engage in AI inference and analyze medical images in real time. Advancements in natural language processing (NLP) can also help the staff generate electronic health records (EHR) during consultation, which not only lightens the administrative burden, but also makes data retrieval and analysis a breeze. The upshot is greater efficiency and making sure that the patients get the full attention that they require.

Depending on the size of the AI workload, the recommended server solution can either be a specialized AI inference platform, to be housed inside a centralized micro data center or server room; or a workstation that can be deployed in the doctor’s office. For the first user environment, GIGABYTE recommends the G293-Z43 GPU Server, which features an industry-leading ultra-dense configuration of sixteen AMD Alveo™ V70 cards in a 2U chassis. The Alveo™ V70 is based on AMD’s XDNA™ architecture, which uses an adaptive dataflow structure that allows the data to pass between the layers of an AI model without relying on external memory. The result is better performance and energy efficiency.

For the second scenario, GIGABYTE has a comprehensive line of W-Series Tower Server / Workstation solutions that brings the computing prowess of enterprise-grade servers straight to your desk. For example, the W771-Z00 runs on AMD Ryzen™ Threadripper™ PRO Processors and supports up to seven GPU expansion cards, or four double-wide (DW) accelerators. This is more than enough processing power to enable real-time AI inferencing during consultation. Inference results may be used to retrain and further optimize the AI models, thus completing the virtuous cycle between AI-assisted consultation and healthcare analytics.

GIGABYTE and MyelinTek’s MLSteam DNN Training System can be used to support NLP and large language model (LLM) applications. Since patient data is sensitive and must be kept confidential, medical staff may not be able to use publicly available generative AI services. For hospitals and clinics eager to host their own AI chatbots, GIGABYTE and MyelinTek can help optimize popular open-source LLMs, such as BLOOM, for the GPU acceleration software platform of the client’s choice, such as AMD ROCm or NVIDIA CUDA. In short, we make sure your hardware and software play nicely together so you can get started on providing AI-assisted medical services hassle-free.

Resources:
What is AI Inference?
What is Natural Language Processing (NLP)?
What is Data Center?
What is Server Room?

Before patients can get the treatment that they need, physicians must arrive at the correct diagnosis in a timely manner. AI can be employed in healthcare analytics by “studying” historical medical data (such as medical images) and learning to recognize the symptoms of diseases with greater speed and accuracy. These AI models can then be used during consultation to make the process more efficient and effective. AI can also reduce administrative work and generate EHR on the fly, giving doctors more time to spend with their patients, while also creating a new trove of digital data that may be used for healthcare analytics further down the line.

To inject AI into healthcare analytics, GIGABYTE Technology offers a complete portfolio of AI Servers that can accelerate AI training by using the most advanced processing units on the market. For example, GIGABYTE’s G593-series can support NVIDIA HGX™ H100 8-GPU computing modules, making these servers some of the most powerful AI training platforms you will find. GIGABYTE servers also support the latest NVIDIA Grace Hopper™ Superchip and AMD Instinct™ MI300A APU, which are a new class of chips that combine CPU and GPU into one package that’s optimized for AI and HPC. Healthcare analytics becomes faster and smarter with the help of these solutions.

For AI-assisted consultation, clients may adopt compact, high-density server solutions if they wish to conduct AI inference at a centralized location, or workstations for on-site computation. GIGABYTE’s G293-Z43 is a perfect fit for the first scenario, as it provides industry-leading compute density by packing sixteen AMD Alveo™ V70 cards in a 2U chassis. On the flip side, GIGABYTE’s W-Series Tower Server / Workstation products can be deployed to bring enterprise-grade computing directly to the doctor’s office. The digital data collected during consultation can then be used to retrain and optimize the AI models.

In addition to its topline hardware, GIGABYTE also provides software solutions through its investee company MyelinTek Inc. GIGABYTE’s MLSteam DNN Training System can give a boost to healthcare analytics because it combines popular deep learning frameworks for medical AI development, like NVIDIA MONAI, with recommended labeling tools and image programs to streamline AI training. In addition, MLSteam DNN Training System can be used for NLP and LLM applications, which is important for healthcare providers that wish to host their own AI to support consultation while protecting sensitive patient data.

Resources:
Tech Guide: To Harness Generative AI, You Must Learn About “Training” & “Inference”
FAQ: 10 Frequently Asked Questions about Artificial Intelligence

The logical next step after diagnosis is treatment. One of the exciting breakthroughs in this field is personalized or precision medicine, which takes the patients’ genes, lifestyles, and living environments into consideration when prescribing medicine. This is different from the traditional one-size-fits-all method, which treats all individuals with the same illness as if they were a homogeneous entity. Personalized medicine is more effective and prevents the waste of precious medical resources.

The ubiquity of the aforementioned electronic health records (EHR) goes a long way toward making sure that patient information can be digitized and analyzed by AI. As previously stated, GIGABYTE offers server solutions and MLOps software for working with EHR. These products deliver the computing prowess necessary for AI to study the data and recommend suitable treatments based on the individual’s medical history.

Secure and reliable data storage is also important to the realization of personalized medicine. Since detailed health records must be maintained for human and robot doctors to prescribe customized treatment, specialized servers are used to build the database and to ensure its availability for instant access.

GIGABYTE Technology’s S-Series Storage Servers bring the latest in data storage tech to healthcare and medicine. For example, the S183-SH0 offers all-flash array (AFA) storage with thirty-two EDSFF E1.S NVMe hot-swappable bays, which take advantage of the latest PCIe Gen5 interface to provide greater storage capacity (up to 240 terabytes) and scalability, while also maintaining the pluses of conventional enterprise-grade 2.5” SSDs. GIGABYTE also works with Graid Technology to provide SupremeRAID™, a software-defined solution that features the security benefits of RAID without impacting CPU performance.

GIGABYTE’s Network Servers can support storage servers by connecting them with compute servers and other external devices. While different categories of servers can fulfill this role—including the storage servers themselves—GIGABYTE’s R-Series Rack Servers are highly recommended for their versatility and flexibility. These servers can accommodate the processors, expansion cards, and drive bays of the clients’ choice, with an eye toward optimizing space allocation on server racks and enhancing the data center’s capabilities.

Resources:
What is NVMe?
What is PCIe?
What is Scalability?
What is RAID?
What is Central Processing Unit (CPU)?

It is conducive for medical personnel to keep tabs on their patients’ recovery process after treatment—if it can be done without intruding on personal privacy or affecting quality of life. Traditionally, patient monitoring was only feasible in the hospital ward, and it was very labor-intensive. Monitoring patients outside of the hospital was almost impossible. AI has changed that.

Inside the patient rooms in a hospital ward, patient safety can be protected with inventions such as GIGABYTE’s Smart Fall Detection System, which utilizes 3D depth sensing technology to detect the patient’s position and motion, without rendering or transmitting footage that may violate personal privacy. The system will notify staff immediately if a fall occurs, and it uses AI to accurately assess the situation and prevent false alarms. In the intensive care unit (ICU), a trained AI model can monitor patients’ electrocardiogram (ECG) and alert staff of any danger. GIGABYTE’s AI training and inference solutions for diagnosis, which we’ve already covered, may serve as the computing platforms for patient monitoring.

Outside of hospitals and clinics, wearable devices and other IoT instruments may facilitate telehealth services. AI can respond to general inquiries and evaluate whether the patient requires a human doctor’s attention. GIGABYTE’s E-Series Edge Servers can help to bring computation closer to the patients and expand telemedicine coverage. These servers offer high compute density, high scalability, and low-latency processing in compact chassis that are convenient for deployment outside data centers. They may serve as the building blocks of a 5G-empowered Multi-access Edge Computing (MEC) network, which can process vast amounts of medical data and render timely and reliable medical services. GIGABYTE’s ARM Servers, which use the same “computing language” as a majority of mobile and wearable devices, are another optimal platform for hosting medical AI on the edge to provide care for recovering patients.

Resources:
What is IoT?
What is Edge Computing?
What is 5G?
What is Multi-access Edge Computing?

Outside of medical facilities, researchers are also using the latest computing platforms to develop better and safer treatments more efficiently. Their focus may be an urgent global healthcare crisis—such as COVID-19—or long-term, chronic illnesses that are taking a toll on an aging society, such as hereditary cardiac diseases. AI and HPC can be employed to dissect the molecular structures of viruses and unhealthy human cells. They can also predict the results of different medications and simulate drug interaction to prevent unintended side effects. The result is we’ll have access to the treatments that we need more quickly, and in a way that fully heals our bodies and protects our health.

In most research institutes, computing clusters are built using multiple servers to ensure that scientists can leverage a complete toolset. All of the aforementioned GIGABYTE hardware and software solutions have a role to play. For instance, H-Series High Density Servers and G-Series GPU Servers excel at accelerated computation, and so they may serve as the compute nodes of a cluster. S-Series Storage Servers are perfect for safely storing the raw data and the precious research results. R-Series Rack Servers can take on the roles of computing, storage, or networking; they can also function as the “head” or “control” node, which is important for managing a large number of servers working in tandem.

This is a good place to mention that GIGABYTE offers GIGABYTE Server Management (GSM), a proprietary multiple server remote management software platform, free of charge. GSM facilitates the management of server clusters over the internet. It includes various system management functions: GSM Server for real-time remote control, GSM CLI for remote monitoring and management, GSM Agent for data retrieval through the OS, GSM Mobile for remote management through a mobile app, and GSM Plugin for real-time monitoring and management with VMware vCenter.

The Rey Juan Carlos University in Madrid, Spain, is one satisfied owner of a GIGABYTE computing cluster, which the researchers designated as “Talos”. Their field of research is cellular aging and reprogramming. They hope to study the process of aging at both the cellular and molecular levels, so that new breakthroughs may be possible in the field of cardiology, which in turn can lead to better treatments for cardiac diseases. Taiwan’s Cheng Kung University (NCKU) used a cluster of four GIGABYTE G482-Z50 GPU Servers to simulate how SARS-CoV-2, the virus that causes COVID-19, reacts to different drugs. This is key to the development of vaccines. For their efforts in this study and other achievements, the NCKU student team won first place at the APAC HPC-AI Competition in 2020.

Resources:
What is Computing Cluster?
What is Node?
Case Study: Researching Cellular Aging Mechanisms at Rey Juan Carlos University
Case Study: GIGABYTE Helps NCKU Train Award-Winning Supercomputing Team

After an illness has been diagnosed, physicians must provide treatment that will set the patient on the path toward recovery. AI can improve the medical treatment that we receive in numerous ways. For example, AI can turn the ideal of personalized medicine into reality, so that patients can get customized care based on their medical history. AI-enhanced patient monitoring helps medical staff keep tabs on recovering patients without disrupting their day-to-day lives. AI can also make drug development faster, safer, and more precise, so that we may finally have the solutions to both global pandemics and age-old diseases.

With regard to personalized medicine, not only will servers powered by the most advanced processors be required to study patient data, high-capacity, high-security storage servers will also be essential to safely store the sensitive information. In addition to its comprehensive line of AI Servers, GIGABYTE Technology offers state-of-the-art Storage Servers to safeguard the data, and Network Servers to complement the compute and storage layers of a data center. By partnering with Graid Technology, GIGABYTE provides SupremeRAID™ to further guarantee data security without impacting CPU performance.

Within a hospital ward, patient monitoring is made possible with GIGABYTE’s AI Servers, supported by nonintrusive monitoring devices like the Smart Fall Detection System, which can keep an eye on patients without violating their privacy. Outside of hospitals, GIGABYTE’s Edge Servers and ARM Servers are recommended for expanding the telehealth network. These products bring computation closer to the patients’ places of residence, and they can connect with patients over the 5G network to enable AI consultation and smart monitoring.

Research centers devoted to drug development usually build a computing cluster to bolster their efforts with AI and HPC. GIGABYTE provides all the server solutions necessary to construct such a cluster: from High Density Servers and GPU Servers for computing, to Storage Servers for data storage, to Rack Servers for computing, networking, storage, and overall cluster management. GIGABYTE’s free and proprietary GIGABYTE Server Management (GSM) software allows for convenient remote cluster management.

Resources:
Tech Guide: Cluster Computing, an Advanced Form of Distributed Computing
Tech Guide: How to Pick the Right Server for AI? (Part 1)

If you want to inject artificial intelligence into healthcare and medicine, you should work with a tech partner that can set you up with the complete hardware and software package. With GIGABYTE Technology, you can expect to benefit from these six advantages:

Humanity will lead happier, healthier lives thanks to the introduction of artificial intelligence into the healthcare and medical industry. Broadly speaking, AI can support diagnosis through the use of AI training, which can advance healthcare analytics; and through AI inference, which can help with decision-making during consultation, as well as decrease the administrative burden. AI can improve treatment by prescribing customized, personalized medicine based on the patient’s individual requirements. It can monitor patients during the recovery process, and it can aid researchers in developing newer, better treatments.

Since AI training and inference is key to diagnosis, GIGABYTE Technology’s H-Series High Density Servers and G-Series GPU Servers, which can support some of the most advanced processors on the market, are highly recommended for supporting diagnosis in healthcare and medicine with AI. GIGABYTE’s W-Series Tower Server / Workstation products can bring data center-grade computing prowess straight to the doctor’s office. With regard to software, GIGABYTE’s MLSteam DNN Training System can expedite medical AI development, and it can support LLM and NLP applications that will handle administrative work and generate EHR while safeguarding patient information.

The abovementioned supercomputing platforms are also ideal for providing treatment, but with a few caveats. For personalized medicine, it is advisable to use GIGABYTE’s S-Series Storage Servers to help store and protect the sensitive medical data. R-Series Rack Servers can fill the role of the network servers that support the compute and storage servers; they may also act as the head or control node in computing clusters that are used to develop new drugs and treatments. To provide round-the-clock patient monitoring, nonintrusive surveillance like GIGABYTE’s Smart Fall Detection System can ensure patient safety without violating personal privacy. GIGABYTE’s E-Series Edge Servers and ARM Servers are optimal for building a comprehensive 5G-empowered Multi-access Edge Computing (MEC) network for telemedicine.

The power of AI can revolutionize the healthcare and medical industry to take better care of our wellbeing. If you are looking for a partner to help you participate in this invigorating trend, we highly recommend that you reach out to GIGABYTE Technology and learn what we can do for you.

Thank you for reading “How to Benefit from AI in the Healthcare & Medical Industry”, a part of the “Power of AI” series by GIGABYTE Technology. We hope this article has been helpful and informative. For further consultation on how you can benefit from AI in your business strategy, academic research, or public policy, we welcome you to reach out to our sales representatives at [email protected]

Resources:
The Power of AI: How to Benefit from AI in the Automotive & Transportation Industry
Tech Guide: How to Pick the Right Server for AI? (Part 2)