Artificial intelligence is being used in the treatment of kidney disease so that it becomes easy for healthcare providers to predict the diagnosis.
FREMONT, CA: With the help of big data, the healthcare sector has successfully entered the new era of technologies where they can enjoy various opportunities to evolve the profession. However, to make use of these technologies, it is necessary to analyze the data, interpret them, and use it to enhance patient care. The healthcare providers have to relate to the various information collected from these large and diverse datasets. The data will help them make smart and informed decisions with the help of artificial intelligence (AI).
AI can be considered the industrial revolution of the fourth generation, and it can impact and transform every sector. This technology can also be used in various parts of the healthcare sector, like kidney care. Artificial intelligence will use algorithms and software principles during kidney care and healthcare issue so that they can estimate the decisions made by the clinicians while analyzing complicated healthcare data. Generally, the computer-based algorithms in the healthcare consist of rules that can encode the expert knowledge on the decisions, and these rules can be used to conclude the particular clinical situation. However, the algorithm of AI learns to form the data without any definite rules.
AI in kidney care
During the big data revolution, large dialysis organizations (LDOs) were used, and it has also offered various epidemiological information. Many kidney disease care organizations have a combination of LDO along with renal care, software tools for nephrologists, specialty pharmacy, outpatient endovascular centers, and many others. LDO can be used for collecting demographic, treatment, clinical, and laboratory de-identified data from numerous patients. This information can be used for training the ML models. Moreover, the data collected from kidney disease care organizations can also be used for developing various ML predictive models that offer support to clinical decisions. The information used in the new technologies like CKD and ESRD can enhance the models applied in care and increase the quality and quantity of the patients' lives.
Another device that uses AI is the CKD progression model. This tool is used to identify the route of the eGFR based on two or more historical values. This model has also been implemented in the EMR system and is utilized in nephrology practices to confirm the patient prognosis. The other models that have been developed consist of end-of-life ML and a prediction model that is required to recognize the reducing trend in patients' functional status on dialysis.