In-Brief

• The most significant developments in medical care are precision medicine for recent years, influences potential growth in symptom-driven medical practice.
• Experimental research design on the development of medicine using artificial intelligence is still challenging in the healthcare field.
• Pubrica helps you to understand the role of artificial intelligence in the production of precision medicine.

Introduction

The core of medical practice has to collect a collection of massive data about the patient’s health significantly fast and making decisions accordingly.  The physicians use artificial intelligence tools for their judgement, problem-solving as they have minimal resources, due to this emerging transformation and disruptive technologies in digital healthcare. Major technologies involved in the process of medicine are genomics, biotechnology, artificial intelligence. The three significant benefits are giving sufficient care to patients, collection of massive data with advanced analytics, production of precision medicine. It’s unnecessary to waste time in developing treatments for huge populations and making medical decisions identifying the physical characteristics of patients. Medicine is growing towards prevention, personalization and precision. Artificial intelligence is the critical tool to achieve modern medicine. Clinical study design should have a clear idea about the precise treatment using artificial intelligence with the help of Pubrica.

The rise of medicine practise

Over the past years, medical care gives only generalized solutions for all the health issues that will treat many patients with similar symptoms. Cough syrup can apply to the majority of coughing masses patients, and it creates allergic reactions to very few people. It is essential to find alternative medicine for such cases or to create an accurate treatment of therapy using emerging technologies. Experiences and available pieces of evidence on the working methods of the medical community begin in the twentieth century. The detection of bacteria or viruses, the development of new pharmaceutical tools and medical techniques using AI is leading the healthcare towards the development of a fresh start of the century. The evidence-based medicine gets a place from the experience-based medicine using ‘trial-and-error’. To prove the efficacy of treatments and diagnostics in scientific research and clinical experimental design, they started using alternative therapies, preferably modern medicines. People with allergic reactions after consuming cough syrups are prescribed not to use it as they found extensive precision medicine for cough. It gives alternative solutions for some medical issues using AI tools. Many disruptive technologies like cheap genome sequencing, advanced biotechnology, health sensors for the patients, data collection about patients health, hand-held medical devices, provides a vast significance in the twenty-first century under the name of digital health with smartphones and digital trackers even at their home. Now the physicians can’t work on the absence of artificial intelligence tools.

Precision is impossible without AI

The National Institutes of Health states that precision of medicine is ‘a developing approach for disease treatment and prevention that calculates individual variability in genes, environment and lifestyle for every patient.This approach helps the doctors and researchers in predicting more accurate treatment and prevention strategies on a particular disease that will work formany people. It requires significant computing power (supercomputers)and algorithms that can learn quickly by themselves at an extensive rate (deep learning) and generally, an approach that uses the cognitive capabilities of physicians on a new trend (AI). The supercomputers have become a battleground for countries demonstrating their power through them. Deep learning algorithms help in diagnoses at least as well as physicians in cardiology, dermatology and oncology. It is essential to emphasize the uses of combining such algorithms under the guidance of physicians. The grand challenge of the biomedical imaging on an international symposium,  metastatic breast cancer is detected in full slide images of the sentinel lymph node. The success rate of winner algorithm is 92.5%. A pathologist independently reviewed the same pictures and got the success rate of 96.6%. The deep learning system’s predictions, the human pathologist’s diagnoses increase the success rate of pathologist’sto 99.5%, an approximately 85% reduction in medical error rate for experimental research design purposes.

Does artificial intelligence end with compassion?

Out of all advantages, ethical considerations and legal issues are there.  It comes to health; this becomes a more significantmoral issue.  More unanswered questions today than we face with public discussions worldwide are there, and this gives a clear image as AI is becoming a reality. AI also has severedisadvantages in the medical sector. Focussing on prediction are mediated based on precedence when it comes to machine learning. Still, algorithms can be underperforming in novel cases of drug side effects or treatment resistance where there is no previous example to build on.

Precision medicine needs a myriad of disruptive technologies to be activated into developing treatments, practising medicine, and providing care. Data analysis should support the skills of physicians and is not meant to replace the traditional physician-patient relationship. The actual experimental research designs will follow all the moral values before the production of an accurate medicine

Conclusion

However, the cultural transformation, digital health, the hierarchy of traditional medicine is transferring into an equal level partnership between patients and doctors. Despite many disruptive technologies, AI has the significant potential to provide this transition by analyzing the vast amounts of patient data and healthcare sectors record in every dimension. AI can only complete its mission if it remains a safe and proven aid in treating patients and improving healthcare sectors for experimental design purposes with the help of pubrica.

References

1. Mesko, B. (2017). The role of artificial intelligence in precision medicine.
2. Ahmed, Z., Mohamed, K., Zeeshan, S., & Dong, X. (2020). Artificial intelligence with multi-functional machine learning platform development for better healthcare and precision medicine. Database, 2020.
3. Krittanawong, C., Zhang, H., Wang, Z., Aydar, M., & Kitai, T. (2017). Artificial intelligence in precision cardiovascular medicine. Journal of the American College of Cardiology, 69(21), 2657-2664.