Publications by authors named "John Nemer"

Objective: To investigate the ability of our convolutional neural network (CNN) to predict axillary lymph node metastasis using primary breast cancer ultrasound (US) images.

Methods: In this IRB-approved study, 338 US images (two orthogonal images) from 169 patients from 1/2014-12/2016 were used. Suspicious lymph nodes were seen on US and patients subsequently underwent core-biopsy.

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Hearing loss is a disabling condition that increases with age and has been linked to difficulties in walking and increased risk of falls. The purpose of this study is to investigate changes in gait parameters associated with hearing loss in a group of older adults aged 60 or greater. Custom-engineered footwear was used to collect spatiotemporal gait data in an outpatient clinical setting.

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Article Synopsis
  • A convolutional neural network (CNN)-based algorithm developed to distinguish atypical ductal hyperplasia (ADH) from ductal carcinoma in situ (DCIS) is validated using a new dataset of 280 mammographic images from 140 patients.
  • The study involved a rigorous analysis of these images, utilizing advanced CNN techniques and standard metrics to assess diagnostic performance, focusing on sensitivity, specificity, and accuracy.
  • Results showed the algorithm achieved a high area under the curve (0.90), with diagnostic accuracy at 80.7%, sensitivity at 63.9%, and specificity at 93.7%, confirming its effectiveness on unseen data.
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Ectopic parathyroid adenomas are a common cause of postsurgical persistent primary hyperparathyroidism. Our case highlights a patient with a negative bilateral 4-gland exploration with follow-up parathyroid 4-dimensional CT and Tc-MIBI SPECT/CT, yielding focal uptake in the right piriform sinus. Subsequent direct laryngoscopy revealed a mass in the piriform sinus, which was resected with surgical pathology yielding parathyroid adenoma.

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The purpose of this article was to analyze trends in follow-up recommendations made on musculoskeletal MRI reports. An IRB-approved retrospective study identified 790 musculoskeletal MRI reports from our database between January 1, 2016, and January 1, 2018, containing follow-up recommendations made by the interpreting radiologist. Metadata were automatically extracted and classification of the recommendations was performed by manual review.

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Article Synopsis
  • The study explored using convolutional neural networks (CNNs) to differentiate between pure Ductal Carcinoma In Situ (DCIS) and invasive DCIS using mammographic images.
  • A total of 246 images from 123 patients were analyzed, applying a deep learning architecture with specific configurations to classify the findings.
  • The CNN achieved a diagnostic accuracy of 74.6% with high specificity (91.6%) but relatively lower sensitivity (49.4%), indicating its potential effectiveness in identifying pure DCIS.
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Purpose: An imaging-based stratification tool is needed to identify melanoma patients who will benefit from anti Programmed Death-1 antibody (anti-PD1). We aimed at identifying biomarkers for survival and response evaluated in lymphoid tissue metabolism in spleen and bone marrow before initiation of therapy.

Methods: This retrospective study included 55 patients from two institutions who underwent 18F-FDG PET/CT before anti-PD1.

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To develop a convolutional neural network (CNN) algorithm that can predict the molecular subtype of a breast cancer based on MRI features. An IRB-approved study was performed in 216 patients with available pre-treatment MRIs and immunohistochemical staining pathology data. First post-contrast MRI images were used for 3D segmentation using 3D slicer.

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Primary carcinoma of the middle ear is extremely rare. A 41-year-old woman with a history of skull base osteomyelitis and chronic suppurative right otitis media presented with 1 month of right-sided facial droop, tearing, and headaches. Initial head CT revealed bony destruction and soft tissue opacification involving the right middle ear.

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Objective: To evaluate the association between Dizziness Handicap Inventory-Screening version (DHI-S) score and spatiotemporal gait parameters using SoleSound, a newly developed, inexpensive, portable footwear-based gait analysis system.

Study Design: Cross-sectional.

Patients: One hundred eighteen patients recruited from otology clinic.

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Objective: Cochlear implantation is associated with poor music perception and enjoyment. Reducing music complexity has been shown to enhance music enjoyment in cochlear implant (CI) recipients. In this study, we assess the impact of harmonic series reduction on music enjoyment.

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The coexpression of the MLL partial tandem duplication (PTD) and the FLT3 internal tandem duplication (ITD) mutations associate with a poor outcome in cytogenetically normal acute myeloid leukemia (AML). In mice, a double knock-in (dKI) of Mll(PTD/wt) and Flt3(ITD/wt) mutations induces spontaneous AML with an increase in DNA methyltransferases (Dnmt1, 3a, and 3b) and global DNA methylation index, thereby recapitulating its human AML counterpart. We determined that a regulator of Dnmts, miR-29b, is downregulated in bone marrow of dKI AML mice.

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