Hydatidiform mole in Aminu Kano teaching hospital, northwestern Nigeria: a five year review. [PDF]
Background: Hydatidiform mole is a benign tumour of the trophoblast tissue and a relatively common gynaecological emergency. It could resolve spontaneously following evacuation, however 9-20% of patients with complete hydatidiform mole go on to have ...
Avidine, AR, Zakari, M
core +2 more sources
Segmentation Network with Compound Loss Function for Hydatidiform Mole Hydrops Lesion Recognition [PDF]
Pathological morphology diagnosis is the standard diagnosis method of hydatidiform mole. As a disease with malignant potential, the hydatidiform mole section of hydrops lesions is an important basis for diagnosis. Due to incomplete lesion development, early hydatidiform mole is difficult to distinguish, resulting in a low accuracy of clinical diagnosis.
arxiv
A Semantic Segmentation Network Based Real-Time Computer-Aided Diagnosis System for Hydatidiform Mole Hydrops Lesion Recognition in Microscopic View [PDF]
As a disease with malignant potential, hydatidiform mole (HM) is one of the most common gestational trophoblastic diseases. For pathologists, the HM section of hydrops lesions is an important basis for diagnosis. In pathology departments, the diverse microscopic manifestations of HM lesions and the limited view under the microscope mean that physicians
arxiv
TUBAL HYDATIDIFORM MOLE: REPORT OF A CASE [PDF]
A case report of the relatively rare condition of a primary hydatidiform mole in the fallopian tube is presented. Key words; Hydatidiform mole Fallopian tube.
M. POUR-REZA
doaj +1 more source
Introduction: Hydatidiform mole is an abnormal pregnancy characterized by hyper-proliferation of trophoblastic cells (both cytotrophoblast and syncytiotrophoblast). If the proliferation phenomenon not well controlled, e.g. due to poor medical health care
Khalil Khashei Varnamkhasti
doaj
MOLE: MOdular Learning FramEwork via Mutual Information Maximization [PDF]
This paper is to introduce an asynchronous and local learning framework for neural networks, named Modular Learning Framework (MOLE). This framework modularizes neural networks by layers, defines the training objective via mutual information for each module, and sequentially trains each module by mutual information maximization. MOLE makes the training
arxiv
Case study: Thyrotoxicosis on women with complete hydatidiform molar pregnancy
Thyrotoxicosis defined as a clinical manifestation of excess circulating thyroid hormone. Epidemiologic investigation reports 0.2% of thyrotoxicosis is caused by hydatidiform mole.
Gagah Baskara Adi Nugraha, Pugud Samodro
doaj +1 more source
Hydatidiform Mole of the Uterus [PDF]
n ...
openaire +3 more sources
Recurrent hydatidiform mole transformed into invasive mole with co-morbid depression- a rare case report [PDF]
The gestational trophoblastic disease is a group of interrelated lesions that arise from abnormal proliferation of placental trophoblast. It comprises of hydatidiform mole (partial or complete), invasive mole, placental site trophoblastic tumor and ...
Bhagat, Nisha, Raj, Rajnish
core +2 more sources
Mole Recruitment: Poisoning of Image Classifiers via Selective Batch Sampling [PDF]
In this work, we present a data poisoning attack that confounds machine learning models without any manipulation of the image or label. This is achieved by simply leveraging the most confounding natural samples found within the training data itself, in a new form of a targeted attack coined "Mole Recruitment." We define moles as the training samples of
arxiv