Artificial Intelligence and Its Growing Role in Diagnosing Neurological Diseases
In recent years, artificial intelligence has become one of the promising tools in the field of medicine, especially in diagnosing neurological diseases such as dementia and Alzheimer’s. These applications have attracted the attention of numerous studies, including a recent study published in the journal Nature Neuroscience.
The Global Prevalence of Dementia
More than 55 million people worldwide suffer from dementia, with over 60% living in low- and middle-income countries. Approximately 10 million new cases are recorded each year, according to the World Health Organization. Combating brain diseases, particularly age-related dementia, is a global priority. Researchers strive to find effective methods for early detection of these diseases and to develop new treatments.
Challenges in Discovering Age-Related Dementia
To date, there are no effective medications for treating age-related dementia, and the disease is often discovered at advanced stages, making traditional treatments less effective. Early detection of dementia can enable patients to live longer without symptoms, thus scientists are trying to develop easy-to-use, effective, and cost-efficient diagnostic tools.
Technology and Artificial Intelligence
Thanks to technological advancements, artificial intelligence can now analyze medical images with unprecedented accuracy. This allows doctors to detect subtle changes in the brain or retina that may indicate the onset of dementia before symptoms become clearly apparent, according to a report by The Washington Post.
Early Diagnosis Using Artificial Intelligence
Artificial intelligence is used to analyze brain scans and retinal imaging, where smart tools can analyze detailed images using techniques like magnetic resonance imaging (MRI) and positron emission tomography (PET). For example, AI can accurately measure the shrinkage of the hippocampus, an early sign of Alzheimer’s disease. This shrinkage may be difficult to notice in traditional examinations, but it can indicate the onset of dementia.
The Role of Artificial Intelligence in Monitoring Disease Progression
AI can also monitor disease progression by analyzing repeated brain images. This helps determine the rate at which affected areas of the brain deteriorate, assisting doctors in evaluating treatment effectiveness and guiding timely therapeutic decisions.
Retinal Imaging Analysis
Retinal imaging has become an important tool for early detection of Alzheimer’s disease. Studies show that changes in the retina may be closely related to those occurring in the brain. AI algorithms analyze retinal images to identify these microscopic changes that may indicate the risk of dementia. This method is considered a low-cost alternative compared to traditional brain scans.
Tracking Speech Patterns
Wearable devices and smart applications powered by artificial intelligence can track a wide range of vital indicators that can reveal early cognitive changes. Dementia is a neurological condition that affects memory, thinking, and the ability to perform daily activities.
Detecting dementia early is one of the significant challenges in neurology. One innovative approach to achieving this goal is analyzing speech patterns using AI technologies. Intelligent algorithms can analyze everyday speech to detect subtle changes that may indicate the onset of dementia.
Speech is a means of expressing thoughts and information. It directly reflects a person’s cognitive state. Changes in speech rate, sentence structure, and vocabulary usage may indicate disorders in brain areas associated with memory and thinking.
AI can accurately and quickly analyze these aspects through natural speech recordings, whether in daily conversations or specific tests. One early indicator of dementia is vocabulary deterioration; individuals with dementia may find it difficult to find appropriate words while speaking, leading to the use of less precise or more generic words.
For instance, instead of using a specific word like “phone,” a person might use a general term like “thing.” AI can detect these changes by comparing words used in conversations over time. Increasing slowness in speech is another sign that may indicate cognitive decline; a person with dementia may show a slower pace in constructing sentences or take longer to respond to questions. Changes in mental processing speed and verbal execution are signs that AI can detect through analyzing speech speed and comparing it to normal benchmarks.
Natural Language Processing Techniques
Natural language processing techniques are used to analyze spoken texts and understand sentence structures and phrases used. Analyzing speech patterns, supported by AI, can reveal early signs of dementia before its clear symptoms manifest. This early detection ability represents a qualitative leap in healthcare, allowing doctors to intervene early and provide treatments. Speech analysis technology is non-invasive, as patients can undergo testing simply by engaging in casual conversation.
Smartphone applications and smart home devices powered by AI can provide continuous monitoring of patients’ health status. These applications can regularly record and analyze audio samples, giving doctors a clear picture of disease progression and treatment impact.
Despite the numerous benefits of this technology, it faces some challenges. Algorithms must be developed to accurately distinguish between natural speech changes and pathological changes while considering linguistic and cultural diversity.
Moreover, patient audio data privacy must be protected, necessitating the development of strict security protocols to safeguard this data from breaches. The cost of developing and implementing this technology may also be high, limiting its availability in some areas.
Predicting Dementia Onset
Analyzing genetic data and biomarkers is an integral part of efforts to achieve early detection of dementia and develop prevention and treatment strategies. Diagnosing dementia poses significant challenges in medical circles due to the complexity of genetic and biological factors influencing the disease. However, advancements in AI technologies may open doors to new methods of analyzing large data sets, such as genetic information and biological markers, enabling doctors to assess an individual’s risk of dementia more accurately.
Genes contain hereditary information that determines many of our traits, including the likelihood of developing certain diseases. One gene linked to Alzheimer’s disease is the APOE ε4 gene; individuals carrying this gene are at a higher risk of developing the disease.
AI can “read” this genetic code with high precision. By analyzing the human genome, intelligent systems can identify genetic patterns associated with dementia, helping to pinpoint individuals at greater risk of onset.
In addition to genes, other biomarkers in the body can indicate the onset of dementia. These biomarkers, such as amyloid and tau proteins, accumulate in the brain before symptoms appear. AI can analyze these markers with high accuracy through examining blood samples, cerebrospinal fluid, and medical images, allowing for early diagnosis in the initial stages of the disease.
Lifestyle Analysis
AI is not limited to analyzing genetic data or biomarkers; it can also integrate these data with other factors such as lifestyle, health habits, and family history. By correlating these factors, intelligent systems can create a more comprehensive picture of an individual’s risk of developing dementia.
Using complex mathematical models, AI can predict the likelihood of an individual developing dementia in the future. These predictions help doctors and patients make informed decisions regarding healthcare plans, such as lifestyle changes or starting pharmacological treatments.
Deep learning, which handles large amounts of complex data, can analyze genetic information with exceptional precision. These models can also address multiple genetic variables and analyze their interactions with other biological factors.
Cognitive Testing
Traditional cognitive function assessments, such as memory and attention tests, are useful tools, but they are often static and lack the adaptability to the individual patient’s abilities. Here, AI can play a role in developing smarter cognitive tests tailored specifically for each individual.
These tests can be conducted using devices like smartphones or tablets, making them more accessible for people in their daily environment. By monitoring subtle performance changes over time, doctors can determine whether a person is experiencing gradual cognitive decline even before it becomes apparent in daily life.
Instead of using traditional tests like memory assessments, AI relies on asking personalized questions for the patient, taking into account factors such as age, educational level, and health background. These smart tests make the assessment more accurate and suited to each individual’s needs.
As AI continues to evolve, these tests may become more accessible, allowing anyone to try them using a smartphone or any other smart device, facilitating doctors’ monitoring of patients’ mental health over an extended period. This continuous monitoring allows for the detection of any minor changes in cognitive performance.
The analysis of data collected from these tests by AI can yield accurate and comprehensive results, offering a clearer picture of brain health compared to traditional methods, thus enabling doctors to make treatment decisions based on reliable information.
One of the most significant advantages of this technology is the ability to detect changes in the brain at very early stages, which can contribute to the early diagnosis of conditions like dementia or Alzheimer’s disease. The results will be more objective and accurate, especially with reduced impact from human biases or temporary factors such as mood or fatigue, ensuring a better assessment of cognitive functions.
Despite the numerous benefits, utilizing AI in cognitive assessment requires handling large amounts of personal data. It is essential to have stringent measures to protect this data and ensure privacy is not violated.
A Promising Future
In the future, smart home devices or AI-enhanced smartphones could continuously monitor individuals’ behaviors and cognitive functions by recording and analyzing their daily patterns.
For instance, walking patterns, speaking styles, or even interactions with the surrounding environment could be monitored in a non-intrusive manner, without the need for frequent visits to the doctor, allowing for the early detection of signs of dementia.
AI will also be able to analyze the data gathered by these smart home devices, and over time, the system can identify subtle changes in speech or movement patterns, such as gradual slowness or hesitation during conversation, which may be early indicators of dementia progression.
Thanks to AI, early diagnosis of dementia may become more common and easier, enabling advanced technology to help doctors detect changes in the brain at early stages, allowing for appropriate treatment to begin before symptoms progress to advanced stages.
