AIMC Topic: Uterine Cervical Neoplasms

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An automatic cervical cell classification model based on improved DenseNet121.

Scientific reports
The cervical cell classification technique can determine the degree of cellular abnormality and pathological condition, which can help doctors to detect the risk of cervical cancer at an early stage and improve the cure and survival rates of cervical...

A multimodal deep learning model for cervical pre-cancers and cancers prediction: Development and internal validation study.

Computers in biology and medicine
BACKGROUND: The current cervical cancer screening and diagnosis have limitations due to their subjectivity and lack of reproducibility. We describe the development of a deep learning (DL)-based diagnostic risk prediction model and evaluate its potent...

Results comparison of cervical cancer early detection using cerviray ® with VIA test.

BMC research notes
OBJECTIVES: This study investigates the performance of artificial intelligence (AI) technology, namely Cerviray AI, compared with Cerviray expert, aiming to compare its sensitivity, specificity, positive predictive value (PPV), and area under the rec...

Integrative machine learning frameworks to uncover specific protein signature in neuroendocrine cervical carcinoma.

BMC cancer
OBJECTIVE: Neuroendocrine cervical carcinoma (NECC) is a rare but highly aggressive tumor. The clinical management of NECC follows neuroendocrine neoplasms and cervical cancer in general. However, the diagnosis and prognosis of NECC remain dismal. Th...

Classification of cervical cancer using Dense CapsNet with Seg-UNet and denoising autoencoders.

Scientific reports
Cervical cancer is one of the deadly diseases that affects women, which requires periodic examinations to identify and treat any cancerous tumors at a preliminary stage. The most prevalent examination tool for cervical cancer prompt identification is...

Bidirectional recurrent neural network approach for predicting cervical cancer recurrence and survival.

Scientific reports
Cervical cancer is a deadly disease in women globally. There is a greater chance of getting rid of cervical cancer in case of earliest diagnosis. But for some patients, there is a chance of recurrence. The chances of treating the Recurrence of cervic...

BMT: A Cross-Validated ThinPrep Pap Cervical Cytology Dataset for Machine Learning Model Training and Validation.

Scientific data
In the past several years, a few cervical Pap smear datasets have been published for use in clinical training. However, most publicly available datasets consist of pre-segmented single cell images, contain on-image annotations that must be manually e...

Development and external validation of a multi-task feature fusion network for CTV segmentation in cervical cancer radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Accurate segmentation of the clinical target volume (CTV) is essential to deliver an effective radiation dose to tumor tissues in cervical cancer radiotherapy. Also, although automated CTV segmentation can reduce oncologists' ...

Can knowledge-based planning models validated on ethnically diverse patients lead to global standardisation of external beam radiation therapy for locally advanced cervix cancer?

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Knowledge-based planning (KBP) can consistently and efficiently create high-quality Volumetric Arc Therapy (VMAT) plans for cervix cancer. This study describes the cross-validation of two KBP models on geographically distinct ...