AI-Powered Solutions To Healthcare Crisis
July 1, 2021
Ancient history – 1725
August 1, 2021AI Today and Tomorrow
The blooming field of Artificial Intelligence (AI) is a branch of computer science that aims to design computer systems that are able to mimic human behavior.(1) The term artificial intelligence was officially born in 1956 in the DARPA – sponsored conference at Dartmouth College in Hanover, New Hampshire; however, the field had been operationally defined many years before.(2) This technology can learn, make predictions, analyze data, reach conclusions, and self-correct itself.(3)
Artificial Intelligence has extended its reach to the medical field. It can solve different medical challenges like predicting upcoming diseases, establishing an accurate and efficient diagnosis, monitoring patients properly, improving safety in hospitals and medical outcomes, maintaining clinical records, and reducing medical costs.
AI in Medicine
There are different types of AI used in the medical field. For example, machine learning (ML), a general-purpose technique based on teaching a computer program to identify patterns in data and later apply that knowledge to new data sets. It can be used to determine the probability of disease, also saving patient records to optimize treatment.(1,3)
Artificial neural networks (ANN) are inspired in the functioning of neurons in the brain, and it has proven to help in forecasting the incidence of disease and decision making. Natural language processing (NLP) works with speech recognition and evaluation of languages supporting and analyzing unstructured data, so it has been used in automated coding and processing of clinical documentation of patients.
Besides, support vector machines (SVM) and heuristics analysis (HA) have been used to manage patients making evidence-based decisions and identify different potential problems, respectively.
AI provides excellent capabilities to perform a required task with lesser involvement of the human being. It can reduce human errors during treatment and surgery and can be used to analyze an individual patient’s genetic profile.(3)
Techniques used by unsupervised machine learning explore enormous amounts of data found in electronic medical records, making it suitable for creating medical tools. Moreover, supervised machine learning algorithms, have been found very useful in radiology and histopathology because of their ability for automated pattern recognition.
The field of surgery has been massively influenced by Machine Learning; being a great example of the application of robotics. In cardiology it has been used for early detection of heart failure, and it continuously makes contributions in cancer research by classifying tumor types and growth rates. In neurology, machine learning tools analyzed blood samples from patients with suspicion of brain tumors using infrared spectroscopy.
COVID-19 has opened the opportunity to use some AI tools that were developed to distinguish COVID-19 patient’s X-ray results from those with other causes of pneumonia or normal lung tissue. These tools helped physicians recognize which COVID-19 patients could be at greater risk of complications and which patients could be in the early stages of sepsis.
There are different types of AI used in the medical field. For example, machine learning (ML), a general-purpose technique based on teaching a computer program to identify patterns in data and later apply that knowledge to new data sets. It can be used to determine the probability of disease, also saving patient records to optimize treatment.(1,3)
Artificial neural networks (ANN) are inspired in the functioning of neurons in the brain, and it has proven to help in forecasting the incidence of disease and decision making. Natural language processing (NLP) works with speech recognition and evaluation of languages supporting and analyzing unstructured data, so it has been used in automated coding and processing of clinical documentation of patients.
Besides, support vector machines (SVM) and heuristics analysis (HA) have been used to manage patients making evidence-based decisions and identify different potential problems, respectively.
AI provides excellent capabilities to perform a required task with lesser involvement of the human being. It can reduce human errors during treatment and surgery and can be used to analyze an individual patient’s genetic profile.(3)
Techniques used by unsupervised machine learning explore enormous amounts of data found in electronic medical records, making it suitable for creating medical tools. Moreover, supervised machine learning algorithms, have been found very useful in radiology and histopathology because of their ability for automated pattern recognition.
The field of surgery has been massively influenced by Machine Learning; being a great example of the application of robotics. In cardiology it has been used for early detection of heart failure, and it continuously makes contributions in cancer research by classifying tumor types and growth rates. In neurology, machine learning tools analyzed blood samples from patients with suspicion of brain tumors using infrared spectroscopy.
COVID-19 has opened the opportunity to use some AI tools that were developed to distinguish COVID-19 patient’s X-ray results from those with other causes of pneumonia or normal lung tissue. These tools helped physicians recognize which COVID-19 patients could be at greater risk of complications and which patients could be in the early stages of sepsis.
Perspectives
The era of AI is nearly unavoidable. It has already been exploited all over the world. This spread of technology into global medicine will assist doctors and physicians in making better clinical decisions in all medical areas. AI will also capably perform a required medical task in less time and at a lower cost, bringing new possibilities in education, training, research and development.
In the upcoming years, AI will help screen and predict disease progression, improve diagnostic accuracy, save and optimize medical resources, facilitate electronic medical records, drug discovery, and repurposing.
The era of AI is nearly unavoidable. It has already been exploited all over the world. This spread of technology into global medicine will assist doctors and physicians in making better clinical decisions in all medical areas. AI will also capably perform a required medical task in less time and at a lower cost, bringing new possibilities in education, training, research and development.
In the upcoming years, AI will help screen and predict disease progression, improve diagnostic accuracy, save and optimize medical resources, facilitate electronic medical records, drug discovery, and repurposing.
“AI is going to help us be better doctors by helping us practice better medicine that is more individualized and more precise. We may have more time to spend face-to-face with the patient, particularly as AI might help us navigate the electronic medical system smartly and more efficiently. That will impact the quality of life of providers and the health of our patients.” Francisco Lopez-Jimenez, MD, MBA.
“AI is going to help us be better doctors by helping us practice better medicine that is more individualized and more precise. We may have more time to spend face-to-face with the patient, particularly as AI might help us navigate the electronic medical system smartly and more efficiently. That will impact the quality of life of providers and the health of our patients.” Francisco Lopez-Jimenez, MD, MBA.