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Towards real time efficient and robust ECoG decoding for mobile brain-computer interface.

Journal of neural engineering
. Decoding locomotion-related brain activities from electrocorticographic (ECoG) signals is essential in brain-computer interfaces (BCIs). Most previous ECoG decoders are computationally demanding and sensitive to noises/outliers. Mobile and robust B...

Mid-level data fusion of pleural effusion SERS spectra and serum CEA levels using machine learning algorithms for precise lung cancer detection.

Nanoscale
Accurate identification of clinically malignant pleural effusions is critical for cancer diagnosis and subsequent treatment planning. Here, surface-enhanced Raman spectroscopy (SERS) data of pleural effusions and serum carcinoembryonic antigen (CEA) ...

Clinical Application of Large Language Models for Intervention Plan Development in Speech-Language Pathology.

American journal of speech-language pathology
PURPOSE: This study investigates the speech and language intervention plan outputs generated by six different artificial intelligence (AI) tools powered by large language models (LLMs), currently available for clinical writing in the field of speech-...

Prospective quality control in chest radiography based on the reconstructed 3D human body.

Physics in medicine and biology
Chest radiography requires effective quality control (QC) to reduce high retake rates. However, existing QC measures are all retrospective and implemented after exposure, often necessitating retakes when image quality fails to meet standards and ther...

Novel composite health assessment risk model for older allogeneic transplant recipients: BMT-CTN 1704.

Blood advances
Allogeneic hematopoietic cell transplantation (allo-HCT) is potentially curative for older adults with hematologic malignancies. Concerns on nonrelapse mortality (NRM) in older adults limit allo-HCT utilization. We executed a prospective, observation...

Prediction of Adolescent Suicide Attempt by Integrating Clinical, Neurocognitive and Geocoded Neighborhood Environment Data.

Schizophrenia bulletin
BACKGROUND AND HYPOTHESIS: Suicide attempt is a complex behavior influenced by a combination of factors including clinical, neurocognitive, and environmental. We aimed to leverage multimodal data collected during pre/early adolescence in research set...

A multi-omics machine learning classifier for outgrowth of cow's milk allergy in children.

Molecular omics
Cow's milk protein allergy (CMA) is one of the most common food allergies in children worldwide. However, it is still not well understood why certain children outgrow their CMA and others do not. While there is increasing evidence for a link of CMA w...

Prediction of tissue and clinical thrombectomy outcome in acute ischaemic stroke using deep learning.

Brain : a journal of neurology
The advent of endovascular thrombectomy has significantly improved outcomes for stroke patients with intracranial large vessel occlusion, yet individual benefits can vary widely. As demand for thrombectomy rises and geographical disparities in stroke...

Artificial intelligence models using F-wave responses predict amyotrophic lateral sclerosis.

Brain : a journal of neurology
Nerve conduction F-wave studies contain crucial information about subclinical motor dysfunction that can be used to diagnose patients with amyotrophic lateral sclerosis (ALS). However, F-wave responses are highly variable in morphology, making wavefo...

Modeling the Determinants of Subjective Well-Being in Schizophrenia.

Schizophrenia bulletin
BACKGROUND: The ultimate goal of successful schizophrenia treatment is not just to alleviate psychotic symptoms, but also to reduce distress and achieve subjective well-being (SWB). We aimed to identify the determinants of SWB and their interrelation...