AIMC Topic: Machine Learning

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A machine learning-based linguistic battery for diagnosing mild cognitive impairment due to Alzheimer's disease.

PloS one
There is a limited evaluation of an independent linguistic battery for early diagnosis of Mild Cognitive Impairment due to Alzheimer's disease (MCI-AD). We hypothesized that an independent linguistic battery comprising of only the language components...

Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma.

Cancer
BACKGROUND: Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represen...

Interpretable Artificial Intelligence: Why and When.

AJR. American journal of roentgenology
The purpose of this article is to discuss the problem of interpretability of artificial intelligence (AI) and highlight the need for continuing scientific discovery using AI algorithms to deal with medical big data. A plethora of AI algorithms are ...

ProNA2020 predicts protein-DNA, protein-RNA, and protein-protein binding proteins and residues from sequence.

Journal of molecular biology
The intricate details of how proteins bind to proteins, DNA, and RNA are crucial for the understanding of almost all biological processes. Disease-causing sequence variants often affect binding residues. Here, we described a new, comprehensive system...

Relation Extraction from Clinical Narratives Using Pre-trained Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Natural language processing (NLP) is useful for extracting information from clinical narratives, and both traditional machine learning methods and more-recent deep learning methods have been successful in various clinical NLP tasks. These methods oft...

Transfer Learning from BERT to Support Insertion of New Concepts into SNOMED CT.

AMIA ... Annual Symposium proceedings. AMIA Symposium
With advances in Machine Learning (ML), neural network-based methods, such as Convolutional/Recurrent Neural Networks, have been proposed to assist terminology curators in the development and maintenance of terminologies. Bidirectional Encoder Repres...

Predicting Wait Times in Pediatric Ophthalmology Outpatient Clinic Using Machine Learning.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Patient perceptions of wait time during outpatient office visits can affect patient satisfaction. Providing accurate information about wait times could improve patients' satisfaction by reducing uncertainty. However, these are rarely known about effi...

SeizureBank: A Repository of Analysis-ready Seizure Signal Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Approximately 60 million people worldwide suffer from epileptic seizures. A key challenge in machine learning ap proaches for epilepsy research is the lack of a data resource of analysis-ready (no additional preprocessing is needed when using the dat...