AIMC Topic: Precancerous Conditions
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A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.
European radiology
Sep 2, 2023
OBJECTIVES: With the popularization of chest computed tomography (CT) screening, there are more sub-centimeter (≤ 1 cm) pulmonary nodules (SCPNs) requiring further diagnostic workup. This area represents an important opportunity to optimize the SCPN ...
Lung-PNet: An Automated Deep Learning Model for the Diagnosis of Invasive Adenocarcinoma in Pure Ground-Glass Nodules on Chest CT.
AJR. American journal of roentgenology
Jul 26, 2023
Pure ground-glass nodules (pGGNs) on chest CT representing invasive adenocarcinoma (IAC) warrant lobectomy with lymph node resection. For pGGNs representing other entities, close follow-up or sublobar resection without node dissection may be appropr...
Artificial intelligence for evaluating the risk of gastric cancer: reliable detection and scoring of intestinal metaplasia with deep learning algorithms.
Gastrointestinal endoscopy
Jun 29, 2023
BACKGROUND AND AIMS: Gastric cancer (GC) is associated with chronic gastritis. To evaluate the risk, the Operative Link on Gastric Intestinal Metaplasia Assessment (OLGIM) system was constructed and showed a higher GC risk in stage III or IV patients...
Early screening of cervical cancer based on tissue Raman spectroscopy combined with deep learning algorithms.
Photodiagnosis and photodynamic therapy
Apr 13, 2023
Cervical cancer is the most common reproductive malignancy in the female reproductive system. The incidence rate and mortality rate of cervical cancer among women in China are high. In this study, Raman spectroscopy was used to collect tissue sample ...
Clinicians' perception of oral potentially malignant disorders: a pitfall for image annotation in supervised learning.
Oral surgery, oral medicine, oral pathology and oral radiology
Mar 7, 2023
OBJECTIVE: The present study aims to quantify clinicians' perceptions of oral potentially malignant disorders (OPMDs) when evaluating, classifying, and manually annotating clinical images, as well as to understand the source of inter-observer variabi...
Deep learning ensemble 2D CNN approach towards the detection of lung cancer.
Scientific reports
Feb 20, 2023
In recent times, deep learning has emerged as a great resource to help research in medical sciences. A lot of work has been done with the help of computer science to expose and predict different diseases in human beings. This research uses the Deep L...
Application of EfficientNet-B0 and GRU-based deep learning on classifying the colposcopy diagnosis of precancerous cervical lesions.
Cancer medicine
Jan 11, 2023
BACKGROUND: Colposcopy is indispensable for the diagnosis of cervical lesions. However, its diagnosis accuracy for high-grade squamous intraepithelial lesion (HSIL) is at about 50%, and the accuracy is largely dependent on the skill and experience of...
Deep learning in CT colonography: differentiating premalignant from benign colorectal polyps.
European radiology
Jan 26, 2022
OBJECTIVES: To investigate the differentiation of premalignant from benign colorectal polyps detected by CT colonography using deep learning.
Deep Learning Reconstruction Shows Better Lung Nodule Detection for Ultra-Low-Dose Chest CT.
Radiology
Jan 18, 2022
Background Ultra-low-dose (ULD) CT could facilitate the clinical implementation of large-scale lung cancer screening while minimizing the radiation dose. However, traditional image reconstruction methods are associated with image noise in low-dose ac...
Cervical cell multi-classification algorithm using global context information and attention mechanism.
Tissue & cell
Nov 20, 2021
Cervical cancer is the second biggest killer of female cancer, second only to breast cancer. The cure rate of precancerous lesions found early is relatively high. Therefore, cervical cell classification has very important clinical value in the early ...
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