PART-II)JOBS FOR YOUTHS, MEDICAL STUDENTS &LONELY PATIENTS: SKILLS TO USE ICT /4IR /VR /IOT/ AI/ 5G & ROBOTS IN HC, DIAGNOSIS, LABS, MEDICARE &SURGERY

NOTE.Worthy audience in each part of this Article we discuss in brief about those opportunities meant for jobless youth & are very easy to learn in few months such as to do as Lab Technicians, Basic Radiology Technician ,Nursing Assistance & Paramedic, IT Computer Science or Healthcare Diplomas Holders, they can Join a Clinic to refine experience meanwhile start online short courses of IT/ digital Techn based image interpretation,OT patient management, wardboys,physiotherapist or general healthcare training,so as to assist doctors & surgeons in the hospital advance technological upgrading.There would be indeed lot of stuff in this Article for regular medical professionals & Healtharec Depts. /Health Secretaries /Ministeries/Advisors which may enable hospitals to start using Smart Healthcare innovation in Pakistani hospital, right from today.(most important and cheap to do is collection /preserving of patient data (history, treatment,medicines and diet ,family diseases,all test reports,surgery,admission vaccination record,job srtress,social life,clinical remarks,biodata,etc,etc)

?????????????????????????????????? ????PART TWO

9.??????Improved Treatments.?The real-world cases of?AI applications in healthcare, advanced technologies are playing an increasingly important role in augmenting medical staff in almost every area of patient treatment.?Patients with?high blood pressure and lung disease can be treated with more accurate data based on an AI-supported magnetic resonance imaging (MRI)-based algorithm of cardiac motion. & diagnose rare DNA based diseases in 2019.?Guo and Li reported?AI-based technologies can greatly improve patient care services in rural farm communities of developing economies.

• AI has been proven to be?especially effective with a large volume of radiology data to improve the quality of care services with medical imaging.?If AI-based software can improve the accuracy of patient diagnoses, then it will greatly help not only patients, but also the work of medical staff. For example,?the frequency analysis of mitosis in cancer cells through images or microscope is a straightforward process, but takes a great deal of time.
• AI software can perform this task with greater accuracy and speed, thus, helping medical staff with their professional work while eliminating some of the drudgeries of tasks.
• AI-supported medical software can get smarter with learning from the increased volume of accumulated data and new medical research.
• The continuous research in the use of?AI systems will greatly augment the work of medical staff as they can alert some areas that humans often miss or help minimize medical errors during the patient treatment.

10.??Improved Patient Engagement and Participation. Some population groups face precarious health, reflecting their vulnerability, in terms of lack of agency or control. Smart technologies promise to transform people's lives from, smart informed consent to the enhanced connectedness with greater computational processing and more complex decision-making they can achieve. This study aims to investigate how smart technology can mitigate vulnerability and improve well-being

• ?Noom, one of the most popular smartphone-based health coaching apps, is a diet app that fully functions as a mobile diabetes prevention program. The company states, “we work with customers across the globe to help them create healthier habits, reduce their risk of chronic health problems, reverse disease, and foster healthier relationships with themselves in the process” . The key to achieving the goals a person sets in using this coaching app, he/she must be fully committed to the program.
• Patient participation in the advanced medical treatment process is imperative for accurate disease diagnosis and patient safety. When patients are encouraged to participate in their medical treatment, they tend to be fully engaged in carrying out their part in the process, which has a positive influence on their satisfaction with the care quality . Patients’ positive experience of their engagement in the treatment process has positive impacts on the treatment result and patients’ safety.
• While, patients may not be familiar with AI or AI-supported medical systems, they are more likely to participate in the system supported treatment process if they learned from the popular media or the attending physician about the possibility of faster and more accurate diagnosis, reduced medical errors, and decrease of the medical cost. With the rapid advances of AI and AI-imbedded medical systems, healthcare systems should develop strategies to inform and educate customers (patients and family members) about the merits and risks of the new systems. Well-informed customers will more willingly participate in the use of AI medical systems, and thus, increase the flexibility of their treatment options.

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11.??AI Applications in Precision Medicine. There are numerous ways AI can positively impact the practice of medicine, whether it's through speeding up the pace of research or helping clinicians make better decisions. Here are some examples of how AI could be used:

• AI In Disease Detection And Diagnosis. Unlike humans, AI never needs to sleep. Machine learning models could be used to observe the vital signs of patients receiving critical care and alert clinicians if certain risk factors increase. While medical devices like heart monitors can track vital signs, AI can collect the data from those devices and look for more complex conditions, such as sepsis. One IBM client has developed a predictive AI model for premature babies that is 75% accurate in detecting severe sepsis.
• Precision Medicine for Personalized Disease Treatment. The Precision medicine could become easier to support with virtual AI assistance. Because AI models can learn and retain preferences, AI has the potential to provide customized real-time recommendations to patients around the clock. Rather than having to repeat information with a new person each time, a healthcare system could offer patients around-the-clock access to an AI-powered virtual assistant that could answer questions based on the patient's medical history, preferences and personal needs.
• Accelerated Drug Development. Drug discovery is often one of the longest and most costly parts of drug development. AI could help reduce the costs of developing new medicines in primarily two ways: creating?better drug designs?and finding?promising new drug combinations. With AI, many of the big data challenges facing the life sciences industry could be overcE
• Evidence-based Insights about Treatments. Integrating medical AI into clinician workflows can give providers valuable context while they're making care decisions. A trained machine learning algorithm can help cut down on research time by giving clinicians valuable search results with evidence-based insights about treatments and procedures while the patient is still in the room with them.
• Drug Management. There is some evidence that AI can help improve patient safety. A?recent systemic review?of 53 peer-reviewed studies examining the impact of AI on patient safety found that AI-powered decision support tools can help improve error detection and drug management.
• Reducing Medication Errors. There are a lot of potential ways AI could reduce costs across the healthcare industry. Some of the most promising opportunities include reducing medication errors, customized virtual health assistance, fraud prevention, and supporting more efficient administrative and clinical workflows.
• Providing Contextual Relevance In Medication Use. One major advantage of deep learning is that AI algorithms can use context to distinguish between different types of information. For example, if a clinical note includes a list of a patient's current medications along with a new medication their provider recommends, a well-trained AI algorithm can use natural language processing to identify which medications belong in the patient's medical history.
• Telemedicine. Telemedicine is?the practice of medicine using technology to deliver care at a distance. A physician in one location uses a telecommunications infrastructure to deliver care to a patient at a distant site. Live video conferencing, mobile health apps, “store and forward” electronic transmission, and remote patient monitoring (RPM)?are examples of technologies used in telehealth.

12. ?Improved Medical Error Reduction and Service Quality

The development of an AI system based on new algorithms and order parameters. When this system was integrated with a deep-learning AI medical program, the highest accuracy rate found was 83.5% when applied to a sample patient group. However, after the system was interfaced with a deep-learning and decision tree AI system, the accuracy rate increased to 87.3%. Recently developed smart AI systems can further reduce the error rate and they are expected to further improve the care service quality.

• Iin China, doctors who performed colonoscopy examinations with the support of AI discovered 20% more polyps than those without. The AI-supported system can find the notoriously small (5 mm or less in size) or early developmental polyps that many gastroenterologists miss during the colonoscopy exams. Therefore, AI systems augment doctors in eliminating problematic small polyps that can cause future problems, improving care service, and reducing medical error possibilities.
• Radiologists are often cited as the most likely medical personnel who will be displaced by AI. This prediction is based on the fact that a radiologist can read 50–100 X-rays a day, while an AI-supported system can read 10–100 times more images. In addition, the accuracy of the AI system is superior to that of radiologists. Thus, when the AI system augments radiologists, doctors can utilize the time saved by the AI system to conduct more friendly and meaningful discussions with patients that can help improve the quality of care service. In addition, with the more accurate data extracted by AI, medical staff can prevent possible medical errors in advance.

13. Improved Operational Efficiency with least Cost.AI-supported medical systems, as discussed above, can handle many diagnostic activities without human intervention. For example, an AI-imbedded pill-cam can replace laborious traditional upper endoscopy to check stomach cancer exa.A new AI-based method to examine the bone marrow structure characteristics to test the acute leukemia, which can replace the high cost conventional methods. These AI systems all help make the diagnosis and treatment processes much more efficient and cost effective.

• AI systems are not exclusively for medical purposes. Some AI systems are designed to support operational innovations to create additional or new value in the value chain of a healthcare organization. AI systems can perform routine operational activities much better and faster than human workers, such as managing maintenance systems, accounting, and information inquiry. AI-enabled chatbots and nursing robots can greatly improve the efficiency of operational processes.
• Clinical Trial Efficiency. A lot of time is spent during clinical trials assigning medical codes to patient outcomes and updating the relevant datasets. AI can help speed this process up by providing a quicker and more intelligent search for medical codes. Two IBM Watson Health clients recently found that with AI, they could?reduce their number of medical code searches by more than 70%.
• AI in medical imaging. AI is already playing a prominent role in medical imaging.?Research has indicated?that AI powered by artificial neural networks can be just as effective as human radiologists at detecting signs of breast cancer as well as other conditions. In addition to helping clinicians spot early signs of disease, AI can also help make the staggering number of medical images that clinicians have to keep track of more manageable by detecting vital pieces of a patient's history and presenting the relevant images to them.

14.??Increased Productivity and New Job Creation. Will robots and AI take over everything that humans are doing currently? The history and evolution of industrial development, from the 1st Industrial Revolution to the fourth Industrial Revolution, have shown that while many routine manual jobs were replaced by technologies, many new jobs have also been created to support productivity increase. For example, although the hard-copy printing business has diminished greatly, many new jobs have been created in digital editing and typography. Many map publishers have closed their doors, on the other hand, numerous new jobs were created to develop navigation and geographic information systems.

• The accuracy rate of diagnosis, in comparison with the collective diagnosis of five expert ophthalmologists, was over 95%. These examples clearly indicate that AI-based systems can improve productivity by decreasing the error ratio, saving the diagnosis and treatment time, and exploring opportunities to expand care services that were not possible in the past.
• ?The potential impact of harnessing AI to analyze medical imaging is huge. With well-established medical companies to up and coming health-tech startups looking to leverage the power of AI, the field is bound to witness tremendous growth in the years to come. If you have questions about how AI can help you streamline operations and cut down on the cost of medical imaging for your practice, with over a decade of specialized experience in healthcare software development and experience of building AI powered software solutions

?14. Reduced Healthcare Cost

Th e ideal healthcare service would include the following: data and evidence-based disease prevention, diagnosis and treatment with the best available technologies, patient-centric customized care, and quality care with empathy from medical staff?If AI can be applied broadly to support such ideal care service, then it can help secure both quality care service and significant savings in medical costs.

According to a report by ABI Research, a consulting firm for marketing research, smart applications of AI in the healthcare industry can save more than?$72 billion by 2023 in the US .ABI Research also stated that major hospitals in the US and Israel already use AI-based programs for disease prevention. The number of AI-supported devices for patient training to prevent chronic diseases (e.g., diabetes, high blood pressure) in these two countries is expected to increase from 53,000 in 2017 to over 4.1 million by 2023, an annual increase of over234 % Thus, AI applications in healthcare can be a major force for reducing medical costs, not only for individual patients but also for society at large. At the national level, such savings can be diverted to prevention of diseases for better quality of life of all citizens.

• Introducing Efficiency in the Field of Radiology. Artificial intelligence is playing a vital role in improving operational efficiency in radiology. By analyzing vast amounts of data in patient’s scans at great speeds and accuracy, AI is successfully supplementing the skills of the radiologist.Which reduces the future need for further rads test or surgical interventions for diagnoses or repetative treatment.
• Intraoperative MRIs for better patient outcomes. Intraoperative MRIs help the surgeons get a better understanding of the tumor size, type and malignancy when resecting cancerous tissues. The Advanced Multimodality Image Guided Operating Suite (AMIGO) is a great tool to assess the completeness of surgery in order to ascertain that all the tumor lesions have been successfully removed. This reduces the future need for future surgical interventions and other treatments for cancer patients.
• ·??????Elimination of human bias in radio diagnosis. Radiologists are human at the end of the day and are prone to human error and bias when making radiological judgment. Repeated tasks over and over again may result in decision fatigue and incorrect diagnosis.AI, on the other hand, is well-suited to handle repetitive work processes, managing large amounts of data, and can provide another layer of decision support to mitigate errors.
• Using AI to prepare 3D models.AI algorithms are being used to construct 3D models out of 2D images. Zebra medical vision is one company that is leveraging machine learning algorithms to create 3D models out of X-ray images. This helps in avoiding the need for MRIs, CT and PET scans. This not only cuts down on the cost of medical imaging but it also ensures that the patients aren’t unnecessarily subjected to high levels of radiation and associated risk of cancer.
• Efficient data management for reduced repeated scans. Inefficient data management is one problem that all hospitals struggle with. The same holds true for radiological images as well. Repeat scans are often ordered when doctor’s or patients are unable to access the prior images. This adds to the cost of medical imaging. A Canadian study found that a diagnostic imaging repository was successful in reducing the instances of repeat exams for patients suffering from biliary cancer by 15-19 percent. I’s ability to organize, store and retrieve large amounts of data comes in helpful in reducing repeated scans. With effective data management comes cost saving as well as reduced exposure of the patients to radiation.

15. Oportunities and Risks Involved in AI Applications in Healthcare

To make AI-applied systems more accurate in making a diagnosis, the market should develop systems for each specialized area designed with machine learning algorithms with a sufficient number of cases that include ethnic and cultural information of patients.

• The increased use of patient data for analytics can increase the cyber security risks for privacy and security, accountability of medical errors , and the possible impact on job loss.
• The old and premitive hospitals culture needs to be replaced gradually with Smart health facilities though the initial cost of setting the AI apparatus/softwares tools seems out of reach of the developing countries.Starting with simple apps of medical /healthcare softwares tools and making ourselves ware of wifi technology through mobile or armband etc.etc, will bear fruit.In long run the saystem may adopt Smart Hospital concept.
• We believe that some of the major positive and negative issues involved with the application of AI-based technologies should be examined to assure a smart use of AI and its wide diffusion in the healthcare industry.

CONTINUED FOR PART THREE SOON