AIMC Topic: Biopsy, Fine-Needle

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Computational Optics Enables Breast Cancer Profiling in Point-of-Care Settings.

ACS nano
The global burden of cancer, severe diagnostic bottlenecks in underserved regions, and underfunded health care systems are fueling the need for inexpensive, rapid, and treatment-informative diagnostics. On the basis of advances in computational optic...

Artificial neural network model to distinguish follicular adenoma from follicular carcinoma on fine needle aspiration of thyroid.

Diagnostic cytopathology
BACKGROUND: To distinguish follicular adenoma (FA) and follicular carcinoma (FC) of thyroid in fine needle aspiration cytology (FNAC) is a challenging problem.

Parathyroid hormone in washout fluid seems to be superior to cytology for localization of the lesion in MIBI-negative patients with primary hyperparathyroidism.

Turkish journal of medical sciences
Background/aim: Primary hyperparathyroidism (PHPT) is characterized by increased calcium (Ca) and parathyroid hormone (PTH) levels. Surgical removal of the culprit hyperfunctioning parathyroid gland is the preferred treatment. In this study, we aimed...

Computer-assisted cytologic diagnosis in pancreatic FNA: An application of neural networks to image analysis.

Cancer cytopathology
BACKGROUND: Fine-needle aspiration (FNA) biopsy is an accurate method for the diagnosis of solid pancreatic masses. However, a significant number of cases still pose a diagnostic challenge. The authors have attempted to design a computer model to aid...

A Computer-Aided Diagnosis System Using Artificial Intelligence for the Diagnosis and Characterization of Thyroid Nodules on Ultrasound: Initial Clinical Assessment.

Thyroid : official journal of the American Thyroid Association
BACKGROUND: An initial clinical assessment is described of a new, commercially available, computer-aided diagnosis (CAD) system using artificial intelligence (AI) for thyroid ultrasound, and its performance is evaluated in the diagnosis of malignant ...

A pre-trained convolutional neural network based method for thyroid nodule diagnosis.

Ultrasonics
In ultrasound images, most thyroid nodules are in heterogeneous appearances with various internal components and also have vague boundaries, so it is difficult for physicians to discriminate malignant thyroid nodules from benign ones. In this study, ...

Combining structural equation modeling analysis with machine learning for early malignancy detection in Bethesda Category III thyroid nodules.

Artificial intelligence in medicine
Atypia of Undetermined Significance (AUS), classified as Category III in the Bethesda Thyroid Cytopathology Reporting System, presents significant diagnostic challenges for clinicians. This study aims to develop a clinical decision support system tha...

From Guidelines to Intelligence: How AI Refines Thyroid Nodule Biopsy Decisions.

Ultrasound in medicine & biology
OBJECTIVE: To evaluate the value of combining American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) with the Demetics ultrasound diagnostic system in reducing the rate of fine-needle aspiration (FNA) biopsies for thy...

Current landscape and emerging opportunities for using telecytology for rapid on-site assessment in cytopathology.

Cancer cytopathology
In recent years, cytopathology practices increasingly are considering the adoption of digital modalities to support remote rapid on-site evaluation (ROSE) of fine-needle aspiration biopsies. Currently, various digital options are available, each of w...

Intelligent diagnosis of thyroid nodules with AI ultrasound assistance and cytology classification.

Frontiers in endocrinology
OBJECTIVE: Accurate evaluation of thyroid nodules is crucial for effective management; however, methods such as ultrasonography and Fine Needle Aspiration Cytology (FNAC) can be subjective and operator-dependent. Indeterminate thyroid nodules (ITNs) ...