Current state and future directions in the diagnosis of amyotrophic lateral sclerosis
M Vidovic, LH Müschen, S Brakemeier, G Machetanz… - Cells, 2023 - mdpi.com
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by
loss of upper and lower motor neurons, resulting in progressive weakness of all voluntary …
loss of upper and lower motor neurons, resulting in progressive weakness of all voluntary …
Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia
With the increase in large multimodal cohorts and high‐throughput technologies, the
potential for discovering novel biomarkers is no longer limited by data set size. Artificial …
potential for discovering novel biomarkers is no longer limited by data set size. Artificial …
Triclustering-based classification of longitudinal data for prognostic prediction: targeting relevant clinical endpoints in amyotrophic lateral sclerosis
This work proposes a new class of explainable prognostic models for longitudinal data
classification using triclusters. A new temporally constrained triclustering algorithm, termed …
classification using triclusters. A new temporally constrained triclustering algorithm, termed …
Automatic prediction of amyotrophic lateral sclerosis progression using longitudinal speech transformer
Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a
more efficient and objective alternative than manual approaches. We propose ALS …
more efficient and objective alternative than manual approaches. We propose ALS …
Predictive modeling of ALS progression: an XGBoost approach using clinical features
This research presents a predictive model aimed at estimating the progression of
Amyotrophic Lateral Sclerosis (ALS) based on clinical features collected from a dataset of 50 …
Amyotrophic Lateral Sclerosis (ALS) based on clinical features collected from a dataset of 50 …
Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges
The relevant study of transcriptome-wide variations and neurological disorders in the
evolved field of genomic data science is on the rise. Deep learning has been highlighted …
evolved field of genomic data science is on the rise. Deep learning has been highlighted …
[HTML][HTML] Research and Application Progress of Radiomics in Neurodegenerative Diseases
J Feng, Y Huang, X Zhang, Q Yang, Y Guo, Y Xia… - Meta-Radiology, 2024 - Elsevier
Neurodegenerative diseases refer to degenerative diseases of the nervous system caused
by neuronal degeneration and apoptosis. Usually, the onset of the disease is insidious, and …
by neuronal degeneration and apoptosis. Usually, the onset of the disease is insidious, and …
Examining ALS: reformed PCA and random forest for effective detection of ALS
Abstract ALS (Amyotrophic Lateral Sclerosis) is a fatal neurodegenerative disease of the
human motor system. It is a group of progressive diseases that affects the nerve cells in the …
human motor system. It is a group of progressive diseases that affects the nerve cells in the …
Implications of artificial intelligence algorithms in the diagnosis and treatment of motor neuron diseases—a review
Motor neuron diseases (MNDs) are a group of chronic neurological disorders characterized
by the progressive failure of the motor system. Currently, these disorders do not have a …
by the progressive failure of the motor system. Currently, these disorders do not have a …
Machine learning for ALSFRS-R score prediction: making sense of the sensor data
R Mehta, A Pramov, S Verma - arXiv preprint arXiv:2407.08003, 2024 - arxiv.org
Amyotrophic Lateral Sclerosis (ALS) is characterized as a rapidly progressive
neurodegenerative disease that presents individuals with limited treatment options in the …
neurodegenerative disease that presents individuals with limited treatment options in the …