Book review: Sujata Mukherjee, Gender, Medicine, and Society in Colonial India: Women’s Health Care in Nineteenth and Early Twentieth-Century Bengal

Sujata Mukherjee, Gender, Medicine, and Society in Colonial India: Women’s Health Care in Nineteenth and Early Twentieth-Century Bengal (New Delhi: Oxford University Press, 2017), xxxv + 223 pp.

Menopausal Women’s Health Care Method Based on Computer Nursing Diagnosis Intelligent System

Taking into account the current feature extraction speed and recognition effect of intelligent diagnosis of menopausal women’s health care behavior, this paper proposes to use a cross-layer convolutional neural network to extract behavior features autonomously and use support vector machine multiclass behavior classifier to classify behavior. Compared with the feature images extracted by traditional methods, the behavioral features extracted in this paper are related to the individual menopausal women and have better semantic information, and the feature description ability in the time domain and the space domain has been enhanced. Through Matlab software, using the database established in this paper to compare its feature extraction time, test classification time, and final recognition accuracy with ordinary convolutional neural networks, it is concluded that the cross-layer CNN-SVM model can ensure the speed of feature extraction. It proves that the method in this paper can be applied to the behavioral intelligent diagnosis system for intelligently nursing menopausal women and has good practical value. This paper designs a home care bed intelligent monitoring system, which can automatically detect the posture of the care bed, and not only can change the posture of the bed under the control of personnel, but also can automatically complete the posture conversion according to the setting. At the same time, the system has the function of monitoring the physical condition of the person being cared for and can detect the heart rate, blood oxygen, and other physiological indicators of the bedridden person. In addition, the system can also provide a remote diagnosis function, allowing nursing staff to remotely view the current state of the nursing bed and the physical condition of the person. After testing, the system works stably, improves the automation and safety of the nursing bed control, and enriches the functions of the nursing bed.

P139 Women's Health Care during COVID-19

Introduction The coronavirus disease 2019 (COVID-19) pandemic is disrupting health services worldwide. Women's health care is often acute and in continual demand, with poor health outcomes seen in women's health in particular in the recent Ebola and Swine flu epidemics. Regrettably, early reports globally and in the UK have shown a rise in the stillbirth rate. We aimed to evaluate the provision of obstetrics and gynaecology services in the UK during the acute phase of the COVID-19 pandemic. Methods We undertook an interview-based national survey of junior doctors in obstetrics and gynaecology in women’s healthcare units in the National Health Service using the network of the UK Audit and Research Collaborative in Obstetrics and Gynaecology. We sought responses on general training, labour ward care, antenatal and postnatal care, benign gynaecology and gynaecology oncology services. Results We received responses from 148/155 units (95%) contacted. Most completed specific training drills for managing obstetric and gynaecological emergencies (89/148, 60.1%) and two-person donning and doffing of personal protective Equipment (PPE) (96/148, 64.9%). The majority of surveyed units implemented COVID-19-specific protocols (130/148, 87.8%), offered adequate PPE (135/148, 91.2%) and operated dedicated COVID-19 emergency theatres (105/148,70.8%). Most units suspended elective gynaecology services (131/148, 88.5%). The 2-week referral pathway for oncological gynaecology was not affected in half of the units (76/148,51.4%), but half reported a planned reduction in oncology surgery (82/148, 55.4%) Discussion Women's health care services have responded well to the acute phase of the COVID-19 pandemic, however further planning is required for the long term.