health with technology

 It's no surprise that technological improvements have a huge impact on our lives. The very development of technology in todays world is the advancement in the healthcare industry.

The essential technologies are laying the groundwork for numerous thriving healthcare innovations that are changing the health industry. To move parallel with evolution, healthcare industries must adopt new technology that will improve the facilities of health, reduce the costs, and provide valued services to patients.

 

 

Overview:

"We believe consumer health innovations - apps, self-diagnosis tools and wearables, - have the potential to enhance the patient-physician interaction and improve overall health outcomes."

- Dr. Glen Stream.

www.runpod.io

 

innovative technologies, paired with a number of new motivations such as technology-centric transformation, not only save costs but also ensure a value-based treatment in the healthcare industry.

AI artificial intelligence, machine learning, and automation have the potential to improve the healthcare centre to the next level.

A study at the University of Michigan shows that digitizing information from conventional paper to electronic health records will reduce the cost of patient care by 3%. They also calculated that each patient would save $5.14 every month.

 

Furthermore, the healthcare sector is adopting revolutionary changes as it seeks innovative ways to deliver the best patient outcomes while reducing overall healthcare costs. What will be the future of the healthcare industry? Let's discuss some promising technologies that are poised to transform the healthcare landscape.

 

 melmod.com

 

1. Artificial Intelligence:

 

Artificial intelligence is playing a crucial role in transforming healthcare. The use of artificial intelligence in the health sector is resolving a number of difficulties that patients, hospitals, and healthcare personnel confront.

 

The use of AI will supply much of the foundation by enabling predictive and precise analytics and clinical decision support systems that will alert providers to concerns far before they would otherwise notice the need to respond.

 

Nowadays, every patient is digitally looked after, which is more responsive and which costs less. Artificial intelligence has a wide range of positive impacts on the healthcare industry, including disease diagnostics, clinical decisions, management, patient monitoring, and wellness management.

 

In today's world, AI is taking over healthcare treatments such as creating better diagnostics, and treatment plans, analyzing data to provide customized and best medication, and monitoring.

 

AI can also to track chronic diseases with accuracy and precision using MRI, ultrasound, CT scans, and x-rays, reducing the cost and time. So, the patients do not have to wait for a diagnosis.

 

According to report by CB Insights, approximately 86% of healthcare provider sectors, science companies, and technology vendors are practising artificial intelligence technology in healthcare. By near future, these organizations will have spent an average of $70+ million on artificial intelligence projects.

 

Let's take a look at some of the ways AI is redefining the healthcare industry:

Using digital automation & artificial intelligence will help in the compilation and analysis of information like (medical records, patient information, and treatment history and previous prescriptions with no time). AI collect, store, re-organize, and trace data in order to provide quick delivery of healthcare services.

Robots can perform X-rays, CT scans, data entry, and other tedious tasks more quickly and precisely. 

Artificial intelligence systems have been developed to analyses data, evaluate reports from a patient's file, and thus assist clinicians in selecting an appropriate treatment plan. The power of AI allows for the early detection of potentially fatal diseases.

AI assists in monitoring a patient's fitness level and sending health updates to the appropriate provider in order to improve or change the patient's treatment plans.

 

2. Blockchain:

Blockchain can be defined as a distributed system that records peer-to-peer transactions, tracks or records changes across networks, and save and exchanges encrypted data for cryptographies. Using blockchain technology will develop the health sector. It will improve the healthcare ecosystem and improve the security, privacy, and interoperability of health data. This technology will provide a new model for health information exchanges (HIE) by making electronic medical records more effective and secure.

 

According to a recent study, it is predicted that by 2025 most healthcare institutes will adopt blockchain technology in their healthcare system.

 

"Adoption of blockchain technologies will be driven by organisations that base their development on providing better quality care, much like the regional health information exchange concept sparked digital health data-sharing. Data exchange worked well in some jurisdictions."

- Brian Behlendorf, in an interview with HITInfrastructure

 

What impact will Blockchain have on healthcare?

Patient privacy and confidentiality are the most pressing issues in healthcare. Those working in healthcare must prioritise and improve security. Despite initiatives, blockchain could be the ideal solution for healthcare.

Collaboration and governance: The amount of available data has grown dramatically in recent years and will continue to grow. Blockchain would improve data governance, increase data ownership, improve interoperability, and result in better data-driven decision making.

Data and analytics: Blockchain technology is defined as a shared, permanent record of peer-to-peer transactions that will provide new insight into how healthcare providers store and exchange data, resulting in greater transparency and trust. Shared data within the virtual database will result in continuous updates, improving real-time analytics.

 

3.Data Science:

 

The volume of health data is increasing and is expected to grow dramatically in the coming years. With over 1.2 billion clinical documents produced in the United States each year, doctors and life scientists have an ocean of big data for their core research. Furthermore, the use of wearable technology generates and shares a massive amount of health-related data. The flood of such data creates new opportunities for more informed healthcare.

 

Data science is an effective healthcare trend for optimising the way hospital operations are managed. With the help of this technology, the industry can find well-organized, cost-effective and feasible ways to tackle vast amounts of existing healthcare data, enhancing its potential to revolutionise healthcare with precise and error-free diagnosis.

 

Gaining in-depth knowledge of the human body is an essential requirement for data scientists and machine learning experts all over the world.

 

Despite having a massive amount of health data at our disposal, diagnostic failure rates remain high. According to a recent study conducted by the National Academies of Sciences, Engineering, and Medicine, approximately 5% of adult patients in the United States are misdiagnosed each year, totaling 12 million people. Furthermore, postmortem examination results research reveals that diagnostic errors are responsible for nearly 10% of patient deaths.

 

Data science plays an important role in predicting a patient with a tumour, the risk of re-admission, or misclassified diagnoses in electronic medical records. Data science will transform the future of healthcare by managing and organising massive amounts of data that will prevent healthcare problems and save millions of lives.

 

How Will Data Science Impact Healthcare?

Disease Management: Using data science to improve diagnostic accuracy and efficiency. Big data also aids in the reduction of medication errors by improving financial and administrative performance and lowering readmissions. Data science in healthcare can improve public health by detecting disease patterns and recording disease outbreaks.

Patient Profile: An EMR contains standard (structured and unstructured) medical data that can be used to identify which patients are at risk and provide appropriate care. Advanced data science can be applied to patient profiles to identify individuals who can benefit from the proactive approach. It also includes a change in lifestyle.

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Saving More lives with AI

Samsung SDS is an abbreviation for Samsung data services, and it is one of about The 20 businesses that comprise the Samsung Group: famous for producing mobile phones, television sets, laptop computers, semiconductors, hard discs, and home electronics refrigerators, dishwashers, and even operating systems in heavy industry, shipbuilding.

SDS's primary product is the operation of data centres, in which they also participate run the Brightics AI Accelerator platform for automated machine learning (AutoML); allowing users to develop AI models much more easily more effectively, precisely, and quickly than ever before

Vice President of Dr Patrick Bangert, Samsung SDSA's Artificial Intelligence, oversees AI engineering and AI sciences teams. The AI engineering team creates. Brightens AI Accelerator provided automated machine learning and distributed training understanding how to accelerate the construction of an AI model. The AI sciences team develops models and expert consulting services. AutoLabel automatically labels prepare datasets for AI by annotating their modelling. They provide the whole range of AI model creation supported by cutting-edge technology and human knowledge. The AI team looks for initiatives both within and outside. They are retaining their position outside the Samsung Group's computer infrastructure and protecting a worldwide presence.

The Human Advantages of Automation of imaging procedure

Samsung SDS has placed a strong emphasis on the healthcare industry, where AI has been used image process automation in regions as in radiology Bangert asserts in no." The medical system" uses ambiguous terms: The planet is overburdened. There aren't any. There are enough physicians to go around. They are greatly influenced by demand due to processes, bureaucracy, and charging procedures. The length of time that any doctor may devote time to genuine patients. Human patients constitute a small proportion of their whole population. Time. A doctor's advice may be incorrect. Around 30% to 35 % of the time, complicated illnesses – identified from complex medical images - are often used as either overlooked or misdiagnosed.

A second opinion is required. already worth a billion dollars today's market." Second thoughts generally originate from other people. Artificial Intelligence offers a neutral third party and a very neutral second. Obtaining a second or third opinion on any method for diagnosing AI eliminates the possibility of any one doctor having a specific level of experience, since

The AI model can handle much more data. Instances and never forgets anything.

The director, Ricky Datta of artificial intelligence engineering at SDS from Samsung, observes;

"Typically, AI models attain precision in the upper 90 percentile, Up to 99.9% of the time in certain circumstances, precision depending on the amount what information is accessible and how If it is of high quality is. By automating these procedures We merely use processes accelerate everything This would be advantageous. greatly reduce the expenditures incurred by both As providers and patient care expenses enhancing diagnostic accuracy and speed increase the total time from the first discomfort point until the beginning of the therapy cycle."

This is true in all medical fields. MRI and CT scan imaging, rather than X-ray Converting ultrasound pictures to standard photographs of the skin Zakia Rahman, clinical assistant professor of dermatology at Stanford University School of Medicine Dermatology, according to the Department of Medicine, "represents two significant new business model boundaries artificial intelligence-powered Patients can snap images of their skin using their phones and acquire immediate, trustworthy diagnoses for any state, and individuals may make use of photographs of to compare their healthy features and bodies for comparing them to society's beauty standards precise cosmetics for a better appearance while not looks unusual The most significant impediment to each include a vast carefully marked

The ultimate AI toolbox from Samsung: 

Brightens Artificial Intelligence Accelerator

The crowning achievement of Samsung's AI efforts is the Brightics AI AutoLabel feature Platform for acceleration. Hankyu Moon, Dr., the team leader behind AutoLabel, reasons this toolbox is so valuable in three sections "First and foremost, in the case of imaging, for An annotation, for example, is often a guidebook. Drawing a circle around something thing is significant, as is categorizing. It has a name. This may be seen in street scenes. Where we may draw the line with autonomous cars an outline around individuals to indicate 'ok, this is it's a person who represents an impediment that the 'The automobile must not collide.'" He describes how these annotations are created. Fast by the AutoLabel feature, which essentially arranges the photographs in the correct order manner with which the information is provided. The trick is that just a handful, generally 10%, of Almost all of the photos in a piece of dataset information - yet locating it is difficult.

The second section, connected to the Moon AutoML Brightics AI Accelerator platform for feature research engineering, entails pre-processing the data in such a manner as to reveal those characteristics of the data that are most important informed, as well as picking the appropriate situations model.

According to Moon, artificial intelligence is a catch-all word for various unique methodologies and model kinds, such as Support vector machines, neural networks, Decision trees or a random forest. It's a situation. of selecting the best one.

Moon said that the third section, AI's role in healthcare imaging, is quite exciting.

Tweaking parameters: "The algorithm that parameters are used to train one of these models by itself. They are often determined by a human, leading to a trial-and-error process of fine-tuning these things properly. AutoML optimizes them for you. automatically."

When it comes to AI accelerators, Another strategy is dispersed training. Datta explains to Samsung: "We use more than one graphics processing unit (GPU). We may employ to assist speed up the procedure. Many of these GPU processors, spread concurrently across multiple to use computers to complete a single training objective." As the go-to toolbox, the AI accelerator The goal of Samsung SDS is to work on all platforms. The efficiency, labelling, and tweaking of the models and distributed training concurrently, such They can "execute the artificial intelligence." process much more swiftly and effectively and arrive at a much more accurate result. Datta concluded, "model in the end."

Healthcare Imaging Difficulties

Nasim Eftekhari, applied AI director Leveraging data science at City of Hope, a world-class cancer research and treatment facility "All," says an organization near Los Angeles. The supervised models that we employ nowadays are training on labelled data. Regardless, Labeling data for training purposes in the industry is generally the most costly component of any AI-based solution. It takes a long time, and since physicians and healthcare are pricey, These photographs must be annotated by specialists. And each picture takes hours and hours to create in terms of the time the City of Hope wants to investigate Using Samsung's active learning in picture auto labelling. There is no doubt about that. About the importance of a deep understanding of pathology picture auto-labelling, We are pleased to investigate the concept of a system that can learn incrementally from "A doctor takes 20 to 30 minutes." minutes to doodle a comment on top of a single picture To train an AI algorithm, to recognize something significant, There are hundreds of such annotated photographs. Required. The procedure is the most time-consuming and costly of the complete course. Workflow for artificial intelligence

It is the most significant impediment that the Brightics AI's AutoLabel feature Accelerator is used to overcome obstacles. Active learning strategy to accelerate that procedure by 90%, hence it will save money the amount of human labour reduced from 100% to 10% - a significant benefit, generally in the tens of millions of dollars for each model.

Dan Waters faces a new task. Business development director and similar goods at Samsung SDS to his residence in the United States, The FDA is the Food and Drug Administration (FDA). Any physical gadget used must be approved. In the medical field, Waters claims, "Because government agencies" are not as sophisticated in their handling of obtaining a physical kind of artificial intelligence, It might take a long time to get a gadget certified. The procedures and staff in place are merely unfamiliar with this new technology. As far as they are concerned, AI is technology. Is still in its early stages."

AI is used outside of healthcare.

"The single greatest problem is climate change." of humanity," Bangert claims.

"AI has a significant role to play in restricting the increase of greenhouse gases. This has and a lot to do with how well we can run things in industries, automobiles, aircraft, and people's homes houses," he went on. Samsung's consumer electronics and semiconductors Home automation gadgets may assist you. Its energy efficiency lowers any individual's entire carbon footprint house or structure. Data centres, particularly AI Workloads, are often blamed for worsening the problem. The contemporary world's climatic effect, yet this is short-sighted. "Other carbon emission sources" Physical world variables are avoided. Because of artificial intelligence, Consider the significant application. You are purchasing on the internet. You visit online, buy something, and the post office delivers it. That is much more. Efficient in terms of greenhouse gas emissions than if you drive your SUV by yourself

"AI can go 20 kilometres to the next mall." to change the world in healthcare diagnosis and therapy as well as clerical procedures, new employment creation and letting current employees improve efficiency."

BANGERT, PATRICK

Vice President of AI,

SDS SAMSUNG

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Predict Industry-Wide Trends Using AI.

 The problem with conventional forecasting is that any effort to foresee a complex system, such as a market or economy, often fails because there are just too many variables and interactions for any basic model to encompass. 

On the other hand, AI Not only can improve product segment forecasts, but it is also more effective across sectors since it can scale to learn from any quantity of data, wherever in the globe. Product specialists who understand how to foresee industry-wide trends may guarantee that they don't spend time on market chances that won't pan out and instead concentrate on the red-hot prospects that will drive company success.

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Smart choice with AI.

 AI is a wide idea. The way we use the phrase changes depending on the circumstance.

In most situations, it refers to machines that can do challenging tasks on their own by learning from data.

As an AI platform, AI sits between you and your data, allowing you to create solutions that address client issues more efficiently than ever before, especially via the use of creative AI. It collects data from every area of the product ecosystem and lets you to ask questions about goods in ways that a person could never, and it converts raw data into useful information that you can use to enhance your products and make smarter choices about how to expand your company.

You may leverage AI to empower product teams with more efficient creative ideation by using the pillars of language comprehension, visual understanding, information extraction, and information organisation. Creative ideation is essential for product development, but it is not the only ability required. Industry trends shift, and it requires a sharp eye to anticipate such shifts and then adjust your product strategy appropriately. While this chapter has discussed how to produce product ideas, you'll want to make sure that you're coming up with product ideas in a trending, feasible market.

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AI use to find market opportunities

Apocalyptic predictions appeared to conclude every discussion of artificial intelligence (AI) only a few years ago. Elon Musk and Stephen Hawking both said that artificial intelligence (AI) may bring about the extinction of the human race in 2014.

But now, things have started to alter. AI has evolved from a terrifying from a black box to a tool that people may use for a number of purposes.

This change results from various technologies finally being thoroughly investigated, especially by Product teams to identify market opportunities Not every industry has used AI in the industry. In actuality, it began as a scientific enigma. A computer scientist in the 1950s John McCarthy sought to investigate the viability of creating robots that could learn. how to carry out activities like play chess by oneself. Nowadays, AI is used widely.

4 Enhancing Market Opportunity Recognition

We'll examine how market opportunity identification may be enhanced using in this chapter. the following issues related to big data and AI

• Locating market possibilities using conventional methods.

• Issues with big data in identifying business opportunities

• Using AI to identify market opportunities

• Examining market reports generated by AI

Identification of market opportunities is crucial for a product team to find an unfulfilled need. It assists them in determining how and against what competition their product will must complete in order to advance. They must determine the competitive environment, specify the value offer by using the market potential.

Additionally, the identification of market opportunities lays the foundation for following chapters. involves developing new concepts and foreseeing market trends

The most crucial thing to keep in mind about using AI to find market opportunities is that it is not about making a magic wand that would quickly identify all of the significant new opportunities. market possibilities. That would be the ideal scenario for a data scientist or software engineer. But When it comes to marketing, where success relies on acting quickly, effectively, and intelligently, those are the qualities of a complete nightmare.

Professionals in marketing and product development face continual deadline pressure. being the first to market with brand-new goods and services. They must act. so efficiently, without compromising quality, and often with constrained resources.

AI gives quickness, effectiveness, and intelligence. models that are installed on scalable servers

AI has the ability to sift through vast amounts of data and see patterns that humans wouldn't.

This implies that it is possible to examine millions of data points in a matter of hours or even seconds.

Numerous industries are using AI, including autonomous cars, face recognition, fraud detection, too.

Marketers may liberate themselves from the constraints by employing AI to identify market opportunity responsibilities associated with manually evaluating and interpreting data on a vast number of potential markets or brand-new product groups. They might delegate work like gathering data and creating ideas for new products to machines. In order to identify market opportunities utilizing AI, it is important to concentrate on actual issues that need effective answers. For instance, marketers could wish to examine their the possible new product categories they may join with their current consumer base - or they might develop unique goods only for their current clients.

Using AI to find new geographic markets for established businesses is another example. even brand-new products - by examining different combinations of consumer demographics, Every area of the globe has different shopping practices, lifestyle preferences, and other factors.

AI may aid marketers in both scenarios by assisting them in making use of the data they currently have. they could not otherwise (by automating certain data collecting chores and others by streamlining). Additionally, it may aid in overcoming certain major obstacles, such as evaluating if a certain market or product category has real scaling potential.

Using AI to identify market opportunities also has the added advantage of allowing you to Use it to distinguish yourself and show that you are committed to innovation. separating your brand(s) from those of rivals, which may help increase brand awareness repute, and overall worth

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