The AI for disease analysis: The Parkinson’s disease edition

Date:

With advanced and progressive AI and ML, the analysis and detection of diseases have become easier. For complex and prolonging diseases, it is still a work in progress, yet the promise looks good.

Error, the major drawback of any analysis, when controlled and manipulated through ML, provides the basis of a strong AI. There are no applications whose algorithms do not produce some margin of error.

Testing and analysis of errors during a medical grade procedure takes time. This can be efficiently reduced by accurate AI and ML applications.

There is no field that has not landed under the umbrella of AI and ML. They are safeguarding the advancements that all the sectors or industries need. Medical institutions are no strangers to it.

In recent studies focusing on incurable diseases, AI and ML applications have accelerated the process of symptom analysis and advanced drug implementation.

Diseases like Scleroderma and Parkinson’s disease have been found to become accustomed to the process of AI and ML.

Parkinson's Disease
Image source: Medicover

The intensity of any progress in an ailment can be almost accurately assessed through AI and ML if the data is not processed at a local level, but rather at a large expanse.

Feeding multiple types of data into an ML to run an AI produces an outcome at that level. The challenge remains to tackle the same symptoms at a local level where the patient numbers are decreasing.

According to the latest reports of AI and ML testing in healthcare, there is a need for advancement in accuracy for a small number of data points. Such challenges delay the progress of various life-threatening diseases, like Parkinson’s disease.

Parkinson’s disease

Parkinson’s disease is a neurological disorder whose onset can be as slow as a slight tremor in one hand. It is a disease that causes stiffness, shaking, and difficulty in maintaining balance and movement.

It is caused by impairment or sudden death of nerve cells in the basal ganglia. The basal ganglia is the area of the brain that controls the movement of the body.

Image source: National Institute of Aging

The death or impairment of the neurons inhibits or disturbs the production of dopamine, which leads to restricted movement ability.

Symptoms of Parkinson’s include:

  • Uncontrollable tremors in the hands, legs, jaw, or head
  • Muscle stiffness for a prolonged period of time.
  • Slow movement
  • Impaired balance leads to a fall
Image source: Dr Prem PIllay

Other symptoms may include:

  • Depression
  • Mood swings
  • Fatigue
  • Skin problems

Dementia of Parkinson’s patients

With the passage of time, patients develop other dysfunctions as well. The cognitive dysfunction can be observed after a year of the onset of physical symptoms of the disease.

This type of dementia is termed Lewy Body Dementia (LBD). The Lewy body denotes the stiffness and difficulty of the body in initiating or continuing movement.

Image source: Medindia

Cognitive disabilities differ in comparison to dementia of Alzheimer’s where physical disabilities occur within a year of the onset of mental issues.

Diagnosis of Parkinson’s disease

Parkinson’s is not a disease that has a cure, nor is it one of those diseases that can be given a valid reason for its occurrence. Scientists are still reveling over the fact that might trigger the decrease or inhibition of dopamine levels drastically and unnecessarily.

Image source: London Neurosurgery Partnership

As of now, it is reported that this disease is found in more men than women. The reason behind this is still unclear.

Since it is a non-genetic disorder, there are no blood or other laboratory tests that can diagnose this disease. The disease is accentuated by the family history and the symptoms shown by the patient.

Moreover, when on medication, if the patient starts to show improvement, it provides positive ground for affirmations about Parkinson’s.

The need for AI and ML

We all know that an application runs on a particular kind of combination of algorithms. The algorithms provide a basis to analyse the data available, the code assessing the data and finally presenting the result intended from the process.

Having learnt the fact that Parkinson’s does not have a blood test and neither a proper explanation as to why this happens, with advanced technologies we just might be able to do so.

The data available for healthcare analysis is massive in comparison to the needs of the hour. AI and ML help in diagnosis, end-to-end drug analysis, enhancements, and flooring positive results of any trial.

Image source: Forbes

This is required specifically for incurable diseases like cancer, scleroderma, Parkinson’s, Alzheimer’s, and many more. Diseases and disorders that do not adhere to the genetic history of the disease, lack proper reasoning behind their existence, lack medicine, and advanced equipment for screening and scanning can be supplemented with AI and ML.

Both AI and ML improvise the direction of the data and experiments, providing space for error and correction. The healthcare industry is far ahead than it used to be with the help of AI and will reach heights unimaginable someday.

Sponsored

Sara Bushra
Sara Bushra
She is a Literature enthusiast who looks at lifestyle with the eyes of fitness whether mental or physical. Preferring to keep herself young forever, she feeds her mind with knowledge and information by reading and her body by regular workouts. Can be actively found behind a book, with a passive drink, coffee or herbal teas.

1 COMMENT

Comments are closed.

Author
Latest

Technology

Business

Entertainment

Share post:

Subscribe

World News

Editor's Choice

Explained: What is moonlighting?
Put simply, moonlighting means taking up a second job or multiple other work assignments apart from an employee's full-time job. This practice is referred to as moonlighting. In other words, it can be termed as dual employment. What is the whole story? Moonlighting is a heated debate topic among Indians, especially Information Technology(IT) sector. So, the moonlighting story popped up in...

Popular