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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Clinical Manifestations
Zahra Amjadi1, Maryam Noroozian1,2,3
1Yaadmaan Institute for Brain, Cognition and Memory Studies, Tehran, Tehran, Iran (Islamic Republic of).
Behavioral variant frontotemporal dementia (bvFTD) is often misdiagnosed due to overlapping symptoms, leading to significant diagnostic delays. Early recognition of subtle signs and advanced tools like AI are crucial for accurate and timely diagnosis of bvFTD.
Area of Science:
- Neurology
- Neuroscience
- Psychiatry
Background:
- Behavioral variant frontotemporal dementia (bvFTD) is a major cause of early-onset dementia characterized by significant personality and behavioral changes.
- Accurate diagnosis of bvFTD is challenging due to symptom overlap with psychiatric disorders and other neurodegenerative conditions.
- Diagnostic delays and misdiagnosis rates in bvFTD are significant clinical concerns.
Purpose of the Study:
- To review recent literature on diagnostic accuracy and challenges in behavioral variant frontotemporal dementia (bvFTD).
- To identify factors influencing diagnostic delays and misdiagnosis in bvFTD.
- To explore the role of emerging technologies and clinical expertise in improving bvFTD diagnosis.
Main Methods:
- A comprehensive literature review was performed using PubMed, Scopus, and Web of Science.
- Studies published between 2020 and 2025 focusing on bvFTD diagnostic pathways, misdiagnosis, and longitudinal assessments were included.
- Emphasis was placed on clinical presentation timelines, diagnostic reclassification, and accuracy predictors like neuroimaging and neuropsychological tests.
Main Results:
- A significant diagnostic delay of 2–5 years is common, with initial misdiagnoses including depression, bipolar disorder, or Alzheimer's disease.
- Subtle early behavioral symptoms (disinhibition, apathy) are often misinterpreted.
- Neuroimaging, neuropsychological evaluations, AI algorithms, and clinician expertise improve diagnostic accuracy.
Conclusions:
- bvFTD is frequently misdiagnosed initially due to overlapping symptoms with other conditions.
- Standardized frameworks and ongoing assessments improve diagnostic accuracy, but delays persist.
- Early recognition of subtle signs, clinician awareness, longitudinal evaluation, and AI are key to overcoming diagnostic challenges in bvFTD.
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