AIMC Topic: Diagnosis, Differential

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A tree-based machine learning model to approach morphologic assessment of malignant salivary gland tumors.

Annals of diagnostic pathology
Malignant salivary gland tumors represent a challenge for pathologists due to their low frequency and morphologic overlap. In recent years machine learning techniques have been applied to the field of pathology to improve diagnostic performance. In t...

Machine Learning Techniques for Differential Diagnosis of Vertigo and Dizziness: A Review.

Sensors (Basel, Switzerland)
Vertigo is a sensation of movement that results from disorders of the inner ear balance organs and their central connections, with aetiologies that are often benign and sometimes serious. An individual who develops vertigo can be effectively treated ...

Automated interpretation and analysis of bronchoalveolar lavage fluid.

International journal of medical informatics
BACKGROUND: The cytological analysis of bronchoalveolar lavage fluid (BALF) plays an essential role in the differential diagnosis of respiratory diseases. In recent years, deep learning has demonstrated excellent performance in image processing and o...

Identification of Benign and Malignant Lung Nodules in CT Images Based on Ensemble Learning Method.

Interdisciplinary sciences, computational life sciences
BACKGROUND AND OBJECTIVE: Under the background of urgent need for computer-aided technology to provide physicians with objective decision support, aiming at reducing the false positive rate of nodule CT detection in pulmonary nodules detection and im...

CT classification model of pancreatic serous cystic neoplasms and mucinous cystic neoplasms based on a deep neural network.

Abdominal radiology (New York)
BACKGROUND: At present, numerous challenges exist in the diagnosis of pancreatic SCNs and MCNs. After the emergence of artificial intelligence (AI), many radiomics research methods have been applied to the identification of pancreatic SCNs and MCNs.

Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.

Radiology
Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires experience and is subject to substantial interreader variability. Purpose To investigate whether a proposed content-based image retrieval (CBIR) of sim...

Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients.

International journal of molecular sciences
Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult...

Deep convolutional neural network-based algorithm for muscle biopsy diagnosis.

Laboratory investigation; a journal of technical methods and pathology
Histopathologic evaluation of muscle biopsy samples is essential for classifying and diagnosing muscle diseases. However, the numbers of experienced specialists and pathologists are limited. Although new technologies such as artificial intelligence a...

Selection, Visualization, and Interpretation of Deep Features in Lung Adenocarcinoma and Squamous Cell Carcinoma.

The American journal of pathology
Although deep learning networks applied to digital images have shown impressive results for many pathology-related tasks, their black-box approach and limitation in terms of interpretability are significant obstacles for their widespread clinical uti...

3D-PulCNN: Pulmonary cancer classification from hyperspectral images using convolution combination unit based CNN.

Journal of biophotonics
Pulmonary cancer is one of the most common malignancies worldwide. Accurate classification of its subtypes is required in differential diagnosis. However, existing algorithms are mostly based on color images, and the improvement of accuracy is quite ...