classification

OBJECTIVE: To investigate the ability of selective measures on the Wisconsin Card Sorting Test-64 (WCST-64) to predict noncredible neurocognitive dysfunction in a large sample of mild traumatic brain injury (mTBI) litigants. METHOD: Participants included 114 adults who underwent a comprehensive neuropsychological examination. Criterion groups were formed based upon their performance on stand-alone measures of cognitive performance validity (PVT). RESULTS: Participants failing PVTs performed worse across all WCST-64 dependent variables of interest compared to participants who passed PVTs...

Next-generation sequencing offers highly multiplexed and accurate detection of nucleic acid sequences but at the expense of complex workflows and high input requirements. The ease of use of CRISPR-Cas12 assays is attractive and may enable highly accurate detection of sequences implicated in, for example, cancer pathogenic variants. CRISPR assays often employ end-point measurements of Cas12 trans-cleavage activity after Cas12 activation by the target; however, end point-based methods can be limited in accuracy and robustness by arbitrary experimental choices...

BACKGROUND AND OBJECTIVES: Patients with IDH1/2 -mutant lower-grade glioma have a high frequency of seizures. We aimed to investigate the correlations between seizures and tumor/patient characteristics and the impact of surgery and adjuvant treatments (AT) on seizure control along the disease trajectory. METHODS: We retrospectively included patients with IDH1/2 -mutant lower-grade glioma who underwent surgery at the neurosurgery divisions of the University of Turin and Milan and were treated at the Division of Neuro-Oncology of Turin...

Anterior clinoid meningiomas are challenging skull base lesions especially when they encase the internal carotid artery and its branches. According to the Al-Mefty classification, type I can originate in the subclinoid dura, type II on the superolateral aspect of the anterior clinoid process, and type III at the optic foramen, with type I being the most often associated with vascular encasement.1,2 We present the case of a 70-year-old patient who presented with visual disturbances revealing a large type I anterior clinoid meningioma encasing the internal carotid artery and its branches...

BACKGROUND: Given the rapid expansion of research into digital health interventions (DHIs) for severe mental illness (SMI; eg, schizophrenia and other psychosis diagnoses), there is an emergent need for clear safety measures. Currently, measurement and reporting of adverse events (AEs) are inconsistent across studies. Therefore, an international network, iCharts, was assembled to systematically identify and refine a set of standard operating procedures (SOPs) for AE reporting in DHI studies for SMI...

OBJECTIVE: Accurate assessment of pressure injuries (PIs) is necessary for a good outcome. Junior and non-specialist nurses have less experience with PIs and lack clinical practice, and so have difficulty staging them accurately. In this work, a deep learning-based system for PI staging and tissue classification is proposed to help improve its accuracy and efficiency in clinical practice, and save healthcare costs. METHOD: A total of 1610 cases of PI and their corresponding photographs were collected from clinical practice, and each sample was accurately staged and the tissues labelled by experts for training a Mask Region-based Convolutional Neural Network (Mask R-CNN, Facebook Artificial Intelligence Research, Meta, US) object detection and instance segmentation network...

OBJECTIVE: Reproducible diagnoses of endometrial hyperplasia (EH) remains challenging and has potential implications for patient management. This systematic review aimed to identify pathologist-specific factors associated with interobserver variation in the diagnosis and reporting of EH. METHODS: Three electronic databases, namely MEDLINE, Embase and Web of Science, were searched from 1st January 2000 to 25th March 2023, using relevant key words and subject headings...

In the event of a widespread radiological incident, thousands of individuals will require rapid assessment of exposure using validated biodosimetry assays to inform clinical triage. In this scenario, multiple biodosimetry laboratories may be necessary for large-volume sample processing. To meet this need, we have developed a high-throughput assay for the rapid measurement of intracellular protein biomarkers in human peripheral blood samples using an Imaging Flow Cytometry (IFC) platform. The objective of this work was to harmonize and validate the reproducibility of our blood biomarker assay for radiation exposure across three IFC instruments, two located at Columbia University (CU) and the third at Health Canada...

To overcome the challenges posed by the complex structure and large parameter requirements of existing classification models, the authors propose an improved extreme learning machine (ELM) classifier for human locomotion intent recognition in this study, resulting in enhanced classification accuracy. The structure of the ELM algorithm is enhanced using the logistic regression (LR) algorithm, significantly reducing the number of hidden layer nodes. Hence, this algorithm can be adopted for real-time human locomotion intent recognition on portable devices with only 234 parameters to store...

Robot-assisted motor training is applied for neurorehabilitation in stroke patients, using motor imagery (MI) as a representative paradigm of brain-computer interfaces to offer real-life assistance to individuals facing movement challenges. However, the effectiveness of training with MI may vary depending on the location of the stroke lesion, which should be considered. This paper introduces a multi-task electroencephalogram-based heterogeneous ensemble learning (MEEG-HEL) specifically designed for cross-subject training...

Mixed-precision Deep Neural Networks (DNNs) provide an efficient solution for hardware deployment, especially under resource constraints, while maintaining model accuracy. Identifying the ideal bit precision for each layer, however, remains a challenge given the vast array of models, datasets, and quantization schemes, leading to an expansive search space. Recent literature has addressed this challenge, resulting in several promising frameworks. This paper offers a comprehensive overview of the standard quantization classifications prevalent in existing studies...

Unknown image deformation and few-shot issues have posed significant challenges to inverse synthetic aperture radar (ISAR) target classification. To achieve robust feature representation and precise correlation modeling, this article proposes a novel two-stage few-shot ISAR classification network, dubbed as robust embedding and manifold inference (REMI). In the robust embedding stage, a multihead spatial transformation network (MH-STN) is designed to adjust unknown image deformations from multiple perspectives...

Graph neural networks (GNNs) have advanced graph classification tasks, where a global pooling to generate graph representations by summarizing node features plays a critical role in the final performance. Most of the existing GNNs are built with a global average pooling (GAP) or its variants, which however, take no full consideration of node specificity while neglecting rich statistics inherent in node features, limiting classification performance of GNNs. Therefore, this article proposes a novel competitive covariance pooling (CCP) based on observation of graph structures, i...

Rhabdomyomatous mesenchymal hamartoma (RMH) typically presents as a congenital midline head and neck cutaneous polyp in infants. Perianal and mucocutaneous lesions have been reported, and recently, acquired adult-onset variants have been proposed. This makes the true prevalence, etiopathogenesis, and clinicopathologic distribution and classification of RMHs in children compared with those in adults uncertain. We performed a retrospective review to highlight the salient histopathologic, histochemical, and immunohistochemical features in RMHs and to emphasize their specific clinicopathologic criteria to avoid diagnostic pitfalls...

BACKGROUND: Limited awareness, social stigma, and access to mental health professionals hinder early detection and intervention of internet gaming disorder (IGD), which has emerged as a significant concern among young individuals. Prevalence estimates vary between 0.7% and 15.6%, and its recognition in the International Classification of Diseases, 11th Revision and Diagnostic and Statistical Manual of Mental Disorders, 5th Edition underscores its impact on academic functioning, social isolation, and mental health challenges...

Although the association between persistent hypertension and the compromise of both micro- and macro-circulatory functions is well recognized, a significant gap in quantitative investigations exploring the interplay between microvascular and macrovascular injuries still exists. In this study, the authors looked into the relationship between brachial-ankle pulse wave velocity (baPWV) and hypertensive retinopathy in treated hypertensive adults. The authors conducted a cross-sectional study of treated hypertensive patients with the last follow-up data from the China Stoke Primary Prevention Trial (CSPPT) in 2013...

BACKGROUND AND AIMS: The new steatotic liver disease (SLD) nomenclature introduced metabolic and alcohol-associated liver disease (MetALD), describing the intersection of metabolic dysfunction-associated steatotic liver disease (MASLD) and alcohol-associated liver disease (ALD). Waitlisting and liver transplantation for MetALD are not well-defined. We aimed to develop and validate an algorithm for identifying SLD phenotypes and assess trends in waitlisting and transplant outcomes. METHODS: We conducted a retrospective cohort study using the United Network for Organ Sharing registry, supplemented with detailed single-center data...

Prediction during language processing has been hypothesized to lead to processing benefits. These possible benefits have led to several prominent theories that center around prediction as an essential mechanism in language processing. Such theories typically assume predicting is better than not predicting at all, but do not always account for the potential processing costs from failed predictions. Predicting wrongly can be costly, but the cost may depend on how wrong the prediction was. Across three experiments, we manipulate cloze probability, semantic relatedness, and language modality (production vs...

Melanotic schwannoma (MS) is a rare and infrequent subtype of schwannoma characterized by cytoplasmic deposits of melanosomes (melanin). Unlike the other schwannomas, it could have malignant transformation. Due to distinctive characteristics and atypical behavior from classic schwannomas subtypes, MS were renamed and reclassified as "melanocytic malignant neural sheath tumor" in the 5th ed. of the World Health Organization's classification of central nervous system tumors in 2021. We present two cases of MS that underwent complete surgical resection...

The study aims to assess the available literature and compare the perioperative outcomes of robotic-assisted partial nephrectomy (RAPN) for posterior-lateral renal tumors using transperitoneal (TP) and retroperitoneal (RP) approaches. Systematically searched the Embase, PubMed, and Cochrane Library databases for literature. Eligible studies were those that compared TP-RAPN and RP-RAPN for posterior-lateral renal tumors. The data from the included studies were analyzed and summarized using Review Manager 5.3, which involved comparing baseline patient and tumor characteristics, intraoperative and postoperative outcomes, and oncological outcomes...