CHU (University Hospital Center) Point G: The department of surgery B is a surgical department of CHU Point G. The department is par excellence a reference department for cases of visceral surgery, cancer surgery, car...CHU (University Hospital Center) Point G: The department of surgery B is a surgical department of CHU Point G. The department is par excellence a reference department for cases of visceral surgery, cancer surgery, cardiovascular surgery, plastic and endocrinology surgery. As a reminder, the CHU Point G is the largest 3rd level referral hospital in Mali. <b><span style="font-family:Verdana;">Aim:</span></b><span style="font-family:Verdana;"> To study the environmental risk factors of stomach cancer in the B surgery department of the Point G University Hospital in Bamako. </span><b><span style="font-family:Verdana;">Patients and Methods:</span></b><span style="font-family:Verdana;"> We performed a cross-sectional study with retrospective collection from January 2008 to June 2018 (126 months). </span><b><span style="font-family:Verdana;">Results: </span></b><span style="font-family:Verdana;">We have identified 380 cases of digestive cancer, including 193 cases of stomach cancer </span><span style="font-family:Verdana;">o</span><span style="font-family:;" "=""><span style="font-family:Verdana;">r 50.79% of digestive cancers. The mean age of the patients was 57.21 ± 13 years. Male sex represented 55% (n = 106). Eating habits were dominated by the consumption of t<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">ô</span> with potash (cereal paste) with 64.76% (n = 185). The main methods of preserving meat and fish were curing and smoking with 57.51% (n = 111). Chronic smoking was found in 24.35% (n = 47), alcohol + tobacco consumption in 2.59% (n = 5). The low socio-economic class represented 126 cases or 65.38%. Housewives and cultivators were respectively 37.82% (n = 73) and 227.97% (n = 54). 20.20% (n = 39) had a history of epigastric pain. Epigastralgia was the most common functional sign with 84.5% of cases (n = 169). An epigastric mass was found in 72 patients or 37.3%. Adenocarcinoma represented 97.4% (n = 188). Palliative surgery concerned the majority of our patients with 64.8% of patients (n = 79). The postoperative consequences were simple in 28.57% of cases (n = 28), the postoperative morbidity and mortality were respectively 33.61% (n = 41), and 23.77% (n = 29). The overall survival rate after surgery was 10.81% at 2 years and 2.94% at 5 years. This rate was 58.83% at 2 years and 28.50% at 5 years after curative surgery. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> The risk factors for stomach cancer are many and varied. Some are particularly present in Africa. Delay in diagnosis due to a belief in traditional healers is common in our community.</span></span>展开更多
Breast cancer remains a significant global health challenge, necessitating effective early detection and prognosis to enhance patient outcomes. Current diagnostic methods, including mammography and MRI, suffer from li...Breast cancer remains a significant global health challenge, necessitating effective early detection and prognosis to enhance patient outcomes. Current diagnostic methods, including mammography and MRI, suffer from limitations such as uncertainty and imprecise data, leading to late-stage diagnoses. To address this, various expert systems have been developed, but many rely on type-1 fuzzy logic and lack mobile-based applications for data collection and feedback to healthcare practitioners. This research investigates the development of an Enhanced Mobile-based Fuzzy Expert system (EMFES) for breast cancer pre-growth prognosis. The study explores the use of type-2 fuzzy logic to enhance accuracy and model uncertainty effectively. Additionally, it evaluates the advantages of employing the python programming language over java for implementation and considers specific risk factors for data collection. The research aims to dynamically generate fuzzy rules, adapting to evolving breast cancer research and patient data. Key research questions focus on the comparative effectiveness of type-2 fuzzy logic, the handling of uncertainty and imprecise data, the integration of mobile-based features, the choice of programming language, and the creation of dynamic fuzzy rules. Furthermore, the study examines the differences between the Mamdani Inference System and the Sugeno Fuzzy Inference method and explores challenges and opportunities in deploying the EMFES on mobile devices. The research identifies a critical gap in existing breast cancer diagnostic systems, emphasizing the need for a comprehensive, mobile-enabled, and adaptable solution by developing an EMFES that leverages Type-2 fuzzy logic, the Sugeno Inference Algorithm, Python Programming, and dynamic fuzzy rule generation. This study seeks to enhance early breast cancer detection and ultimately reduce breast cancer-related mortality.展开更多
文摘CHU (University Hospital Center) Point G: The department of surgery B is a surgical department of CHU Point G. The department is par excellence a reference department for cases of visceral surgery, cancer surgery, cardiovascular surgery, plastic and endocrinology surgery. As a reminder, the CHU Point G is the largest 3rd level referral hospital in Mali. <b><span style="font-family:Verdana;">Aim:</span></b><span style="font-family:Verdana;"> To study the environmental risk factors of stomach cancer in the B surgery department of the Point G University Hospital in Bamako. </span><b><span style="font-family:Verdana;">Patients and Methods:</span></b><span style="font-family:Verdana;"> We performed a cross-sectional study with retrospective collection from January 2008 to June 2018 (126 months). </span><b><span style="font-family:Verdana;">Results: </span></b><span style="font-family:Verdana;">We have identified 380 cases of digestive cancer, including 193 cases of stomach cancer </span><span style="font-family:Verdana;">o</span><span style="font-family:;" "=""><span style="font-family:Verdana;">r 50.79% of digestive cancers. The mean age of the patients was 57.21 ± 13 years. Male sex represented 55% (n = 106). Eating habits were dominated by the consumption of t<span style="font-family:Verdana, Helvetica, Arial;white-space:normal;background-color:#FFFFFF;">ô</span> with potash (cereal paste) with 64.76% (n = 185). The main methods of preserving meat and fish were curing and smoking with 57.51% (n = 111). Chronic smoking was found in 24.35% (n = 47), alcohol + tobacco consumption in 2.59% (n = 5). The low socio-economic class represented 126 cases or 65.38%. Housewives and cultivators were respectively 37.82% (n = 73) and 227.97% (n = 54). 20.20% (n = 39) had a history of epigastric pain. Epigastralgia was the most common functional sign with 84.5% of cases (n = 169). An epigastric mass was found in 72 patients or 37.3%. Adenocarcinoma represented 97.4% (n = 188). Palliative surgery concerned the majority of our patients with 64.8% of patients (n = 79). The postoperative consequences were simple in 28.57% of cases (n = 28), the postoperative morbidity and mortality were respectively 33.61% (n = 41), and 23.77% (n = 29). The overall survival rate after surgery was 10.81% at 2 years and 2.94% at 5 years. This rate was 58.83% at 2 years and 28.50% at 5 years after curative surgery. </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> The risk factors for stomach cancer are many and varied. Some are particularly present in Africa. Delay in diagnosis due to a belief in traditional healers is common in our community.</span></span>
文摘Breast cancer remains a significant global health challenge, necessitating effective early detection and prognosis to enhance patient outcomes. Current diagnostic methods, including mammography and MRI, suffer from limitations such as uncertainty and imprecise data, leading to late-stage diagnoses. To address this, various expert systems have been developed, but many rely on type-1 fuzzy logic and lack mobile-based applications for data collection and feedback to healthcare practitioners. This research investigates the development of an Enhanced Mobile-based Fuzzy Expert system (EMFES) for breast cancer pre-growth prognosis. The study explores the use of type-2 fuzzy logic to enhance accuracy and model uncertainty effectively. Additionally, it evaluates the advantages of employing the python programming language over java for implementation and considers specific risk factors for data collection. The research aims to dynamically generate fuzzy rules, adapting to evolving breast cancer research and patient data. Key research questions focus on the comparative effectiveness of type-2 fuzzy logic, the handling of uncertainty and imprecise data, the integration of mobile-based features, the choice of programming language, and the creation of dynamic fuzzy rules. Furthermore, the study examines the differences between the Mamdani Inference System and the Sugeno Fuzzy Inference method and explores challenges and opportunities in deploying the EMFES on mobile devices. The research identifies a critical gap in existing breast cancer diagnostic systems, emphasizing the need for a comprehensive, mobile-enabled, and adaptable solution by developing an EMFES that leverages Type-2 fuzzy logic, the Sugeno Inference Algorithm, Python Programming, and dynamic fuzzy rule generation. This study seeks to enhance early breast cancer detection and ultimately reduce breast cancer-related mortality.
