scholarly journals A Case Study of a Brain Tumor in an Adult Woman Revealed by Spasms Immediately Following Cesarean Section

2017 ◽  
Vol 37 (7) ◽  
pp. 731-734
Author(s):  
Munenori KUSUNOKI ◽  
Takeshi UMEGAKI ◽  
Miki TAMAI ◽  
Yuki NIKAIDO ◽  
Makiko MIKAMI ◽  
...  
Keyword(s):  
Brain Tumor ◽  
Cesarean Section ◽  
Adult Woman

scholarly journals Leve de foetus

1970 ◽  
Vol 71 ◽  
pp. 85-98
Author(s):  
Jolien Gijbels
Keyword(s):  
Nineteenth Century ◽  
Cesarean Section ◽  
Medical Practice ◽  
Religious Beliefs ◽  
Codes Of Conduct ◽  
Unborn Fetus

This article discusses how Belgian doctors dealt with religious beliefs in their medicalpractice in the nineteenth century, using the medical discussion of the cesarean section asa case study. In this period doctors faced a dilemma as cesareans were highly mortal forwomen and other altemative operations had fatal consequences for the fetus. Whereasmost Catholic physicians preferred the cesarean section, liberal practitioners often saw noharm in sacrificing the unborn fetus in order to save the mother. By analyzing the argumentsand codes of conduct of Belgian doctors I will show how they demarcated boundariesbetween religious beliefs and their medical practice.

scholarly journals Framework for comprehensive enhancement of brain tumor images with single-window operation

2020 ◽  
Vol 10 (1) ◽  
pp. 801
Author(s):  
Deepthi Murthy T. S. ◽  
Sadashivappa G.
Keyword(s):  
Brain Tumor ◽  
Image Enhancement ◽  
Medical Image ◽  
Significant Contribution ◽  
Linear Filter ◽  
Radiological Images ◽  
Multi Level ◽  
Image Enhancing ◽  
Non Linear Filter

Usage of grayscale format of radiological images is proportionately more as compared to that of colored one. This format of medical image suffers from all the possibility of improper clinical inference which will lead to error-prone analysis in further usage of such images in disease detection or classification. Therefore, we present a framework that offers single-window operation with a set of image enhancing algorithm meant for further optimizing the visuality of medical images. The framework performs preliminary pre-processing operation followed by implication of linear and non-linear filter and multi-level image enhancement processes. The significant contribution of this study is that it offers a comprehensive mechanism to implement the various enhancement schemes in highly discrete way that offers potential flexibility to physical in order to draw clinical conclusion about the disease being monitored. The proposed system takes the case study of brain tumor to implement to testify the framework.

scholarly journals Obesity in adult woman and risk for cardiometabolic disease. Case study in Rabat city

2022 ◽  
Vol 14 (1) ◽  
pp. 134
Author(s):  
S. Bayna ◽  
A. Derouiche ◽  
I. Bennis ◽  
N. Elghoulam ◽  
A. Bennis
Keyword(s):  
Adult Woman ◽  
Cardiometabolic Disease ◽  
Disease Case

scholarly journals Lingering Identity as Chronically Ill and the Unanticipated Effects of Life-Changing Precision Medicine in Cystic Fibrosis: A Case Report

2021 ◽  
Vol 8 ◽  
pp. 237437352199697
Author(s):  
Sigrid Ladores ◽  
Morgan Polen
Keyword(s):  
Mental Health ◽  
Cystic Fibrosis ◽  
Case Report ◽  
Precision Medicine ◽  
Drug Combination ◽  
Genetic Disease ◽  
Chronically Ill ◽  
Adult Woman ◽  
Efficacy And Safety

Cystic fibrosis (CF) is the leading genetic disease among Caucasians; however, advances in diagnosis and treatment have improved both quality and quantity of life for those affected. A remarkable recent discovery is the triple-drug combination, elexacaftor/tezacaftor/ivacaftor, which has been touted as a “miracle drug” for CF because of its demonstrated efficacy and safety. This case study reports on an adult woman with CF who experienced positive life-changing results from elexacaftor/tezacaftor/ivacaftor, and yet discovered that she lived in fear that its effectiveness would diminish, and her debilitating symptoms would return. Her lingering identity as chronically ill tainted her view of her new life with skepticism and pervasive anxiety. This case highlights a critical need to engage in early, regular and sensitive discussions with patients before initiating treatments that may affect their emotional and mental health and provide referrals or services to meet those emergent needs.

scholarly journals Deep Learning in Oncology- A Case Study on Brain Tumor

2018 ◽  
Vol 3 (1) ◽  
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Brain Tumor ◽  
Early Detection ◽  
Error Rate ◽  
High Capacity ◽  
Tumor Detection ◽  
Tumor Diagnosis ◽  
The Brain

The brain tumor detection continues to be a challenge owing to the complexity of its symptoms. The research era indicates the tumor diagnosis and identification of tumor exact indicators are still uncertain. These tumors can appear anywhere in the brain and have any kind of shape, size, and contrast. The brain tumor exploration with deep learning is a solution for flexible, high capacity and extreme efficiency. The deep learning is an application of the artificial intelligence with multiple layers helping to predict the outcome of the disease early detection. This paper presents an approach to recognize the indicators and show that deep learning drops error rate for brain tumor diagnoses by 80%.

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