Synthetic Nerve organs Systems within Cardiac Care

A type that evolved out of Artificial Intelligence is Artificial Neural networks (ANN), often interchangeably referred to as Neural Networks. It is just a mathematical or computational model that processes interconnected data (artificial neurons) to find a pattern for the reason that data. In this method you’ve input data, that goes via a connectionist approach to output data. The system adapts and learns through the great number of data that flows through it. The effect is a specialist decision making, or even predicting system, with a near 100% accuracy. Small wonder, clinicians have now been using AI and expert systems to offer better and timely healthcare with their patients.

In a study through the late 1990s, researchers Lars Edenbrandt, M.D, Ph.D., and Bo Heden, MD., Ph.D., of the University Hospital, Lund, Sweden, ventured to add 1,120 ECG records of Heart Attack patients, and 10,452 records of normal patients. The neural networks were found to manage to utilize this input data, and set up a relationship and pattern. This leaning phase was internalized by the device, and started identifying patients with abnormal ECGs with a 10% better accuracy than most clinicians/cardiologists on staff.

These are other factors in determining Heart Attacks, a fascinating research work have been published in a scientific journal from the Inderscience group, the International Journal of Knowledge Engineering and Soft Data Paradigms (IJKESDP) underneath the name “A computational algorithm for the risk assessment of developing acute coronary syndromes, using online analytical process methodology” (Volume 1, Issue 1, Pages 85-99, 2009). Four Greek researchers had ventured to produce a computational algorithm that evolved out of a far more current technique, namely Online Analytical Processing (OLAP). They used this methodology to create the foundations of a “Heart Attack Calculator” ;.The main advantage of OLAP is that it provides a multidimensional view of data, which allows patterns to discerned really large dataset, that could have been otherwise remained invincible. It will take into consideration numerous factors and dimensions, while making an analysis. The study team obtained data from about 1000 patients which were hospitalized because of outward indications of best cardiology hospital in hyderabad Acute Coronary Syndrome. This data included details on the family history, physical activities, body mass index, blood pressure, cholesterol, and diabetes level. This was then matched to a different pair of similar multi dimensional data from several healthy individuals. All of this data were used as inputs to the OLAP process, to explore the role of those factors in assessing cardiovascular disease risk. At various levels of the factors, intelligence could be gathered to be used as a variety of dimensions, for future diagnosis of the extent of risk.

The ANN is more a “teachable software”, that absorbs and learns from data input. When properly computed, even at a quick pace with a tried and tested algorithm, it develops patterns within the input data, or a variety of multiple data dimensions or factors, to which confirmed situation could be compared to, and a prognosis declared.

In 2009, some researchers in Mayo Clinic studied 189 patients with device related Endocarditis diagnosed between 1991 and 2003. Endocartitis is an infection relating to the valves and occasionally the chambers of one’s heart, which are often caused because of implanted devices in the heart. The mortality of due to the infection could be as high as 60%. The diagnosis of this infection required transesophageal echocardiography, which will be an invasive procedure involving the usage of an endoscope and insertion of a probe down the esophagus. Naturally, this is a risky, uncomfortably and expensive procedure. The researchers at Mayo, fed the data from these 189 patients int the ANN, and had it undergo three separate “trainings” to master to judge these symptoms. Upon being tested with different sample populations (only known cases, and a overall sample of a variety of both known and unknown cases), the most effective trained ANN could identify Endocarditis cases very effectively, thus eliminating the requirement for this invasive procedure.

With modern day e-health becoming more and more data centric, access to relevant patient data is gradually becoming extremely convenient. AI and Expert systems having its ANN and computational algorithms, has tremendous opportunities to speed up diagnosis, and effect patient care with speed and more and more accuracy. As AI advances, it will be interesting to observe it marks its footprints in Cardiovascular, Neuro, Pulmonary, and Oncology diagnosis and care.