Investigating the detection of breast cancer with deep transfer learning using ResNet18 and ResNet34.

A lot of underdeveloped nations particularly in Africa struggle with cancer-related, deadly diseases. Particularly in women, the incidence of breast cancer is rising daily because of ignorance and delayed diagnosis. Only by correctly identifying and diagnosing cancer in its very early stages of development can be effectively treated. The classification of cancer can be accelerated and automated with the aid of computer-aided diagnosis and medical image analysis techniques. This research provides the use of transfer learning from a Residual Network 18 (ResNet18) and Residual Network 34 (ResNet34) architectures to detect breast cancer. The study examined how breast cancer can be identified in breast mammography pictures using transfer learning from ResNet18 and ResNet34, and developed a demo app for radiologists using the trained models with the best validation accuracy. 1, 200 datasets of breast x-ray mammography images from the National Radiological Society's (NRS) archives were employed in the study. The dataset was categorised as implant cancer negative, implant cancer positive, cancer negative and cancer positive in order to increase the consistency of x-ray mammography images classification and produce better features. For the multi-class classification of the images, the study gave an average accuracy for binary classification of benign or malignant cancer cases of 86.7% validation accuracy for ResNet34 and 92% validation accuracy for ResNet18. A prototype web application showcasing ResNet18 performance has been created. The acquired results show how transfer learning can improve the accuracy of breast cancer detection, providing invaluable assistance to medical professionals, particularly in an African scenario.

Participant Evaluation of a Multi-disciplinary Oncology Preceptorship Training Program for Oncology Health Professionals from Kumasi, Ghana.

A critical shortage of skilled healthcare workers is a primary cause of disparate global cancer outcomes. We report participant evaluation of a multidisciplinary preceptorship program. In collaboration with the city of Kumasi, Ghana, Mayo Clinic and the City Cancer Challenge hosted a preceptorship program for comprehensive multidisciplinary breast and cervix cancer training. A total of 14 healthcare workers from Kumasi received two weeks of training at Mayo Clinic in November and December 2021. Each participant and preceptor were requested to complete an anonymous post-participation survey. Of the 14 trainee participants, 10 (71%) completed the survey. All respondents found the program "valuable and applicable to their clinical practice." Ninety percent reported they were able to "review effective and critical elements in the development and expansion of the multidisciplinary team" and able to "solve practical clinical cases as a team". General themes of satisfaction included: (1) organization and administration, (2) clinical observations and demonstrations, (3) guidelines development, and (4) recognizing the central importance of cultivating a team-based approach. Of the 40 preceptors, 16 (40%) completed the survey. All respondents reported they felt the training would meaningfully "influence patient care in Ghana", that participation "added value or joy to their clinical practice," and all wished to "participate in future preceptorship programs". After a focused two-week program, trainees reported high satisfaction, usefulness from observing specialized cancer care, and value in closely observing a multidisciplinary oncology team. Preceptors reported the experience added joy and perspective to their clinical practice and wished to participate in future programs.

Intermittent Preventive Treatment of Malaria in Pregnancy with Sulphadoxine-Pyrimethamine and its Associated Factors in the Atwima Kwanwoma District, Ghana.

Background: Intermittent preventive treatment of malaria in pregnancy with Sulphadoxine-Pyrimethamine (IPTp-SP) tablets is one of the recommended interventions to reduce the burden of malaria on both the pregnant woman and the unborn child. The aim of this study was to assess the prevalence of IPTp-SP uptake and its associated factors in the Atwima Kwanwoma District of Ashanti Region, Ghana. Methods: The study was cross sectional. A structured questionnaire was administered to 394 respondents, comprising pregnant women in their last two months of pregnancy and nursing mothers who delivered within three months prior to the study. Medical records of the respondents were also reviewed. Descriptive statistics such as simple proportions, and averages were computed. Chi-square test and multiple logistic regression analysis were performed to determine factors associated with IPTp-SP uptake. Results: The average age of the respondents was 28.2 (±5.9) years. Almost all of the respondents (98%) had received SP at the time of the study. Fifty percent received their first dose of SP between 16 and 19 weeks of gestation. The multiple logistic regression analysis showed a statistically significant association between IPTp-SP uptake and educational level, time of first ANC visit, number of ANC visits and receiving education on SP prior to the administration of the drug. Conclusion: Education on SP use should be intensified at all levels of the health system. Early initiation of ANC is also recommended for optimal uptake of IPTp-SP. More research is needed to understand factors affecting the uptake of SP during pregnancy in the country.