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.
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 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.
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
Other symptoms may include:
- Mood swings
- 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.
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.
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.
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.