Automated Lung Cancer Segmentation in Tissue Micro Array Analysis Histopathological Images Using a Prototype of Computer-Assisted Diagnosis.

BACKGROUND: Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. OBJECTIVE: Develop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images. METHOD: The prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images. RESULTS: The system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue. CONCLUSION: The computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer.

The psychological and emotional impact of coronavirus disease on COVID-19 patients in Najran Province, Saudi Arabia: An exploratory study.

BACKGROUND: The COVID-19 pandemic contributed to a significant mental health crisis and caused a widening economic crisis, growing financial loss, and numerous uncertainties. This pandemic brought alarming implications and overall increased risk for psychiatric illness. This study explores the psychological impact experienced by patients who tested positive from coronavirus in the Najran region, Saudi Arabia. DESIGN AND METHODS: This exploratory analysis included 210 COVID-19 positive patients. The study was conducted during a six-month period starting from March to September 2020, in two tertiary government hospitals in Najran, Saudi Arabia. Samples were selected using purposive sampling; survey questionnaire and face-to-face interview to collect the data. Statistical data were calculated using IBM SPSS v. 2.0 to compute the following statistical formulas: percentage distribution, mean, standard deviation, and Chi-square test of independence. RESULTS: The findings of this study revealed that the majority of COVID-19 positive patients were middle-aged adults (n=98 or 46.7%), male (n=178 or 84.8%), and were non-Saudi nationals (n=132 or 62.9%). It was found out that COVID-19 patients experienced bothersome behaviour at a very high level (x̅=2.63±0.6734). Meanwhile, depression (x̅=2.51±0.7070), worry (x̅=2.23±0.8811), and anxiety (x̅=2.21±0.8719) was only at a high level. CONCLUSIONS: The study revealed that the majority of participants had high levels of depression, anxiety and bothersome behaviours. However, demographic characteristics like age, sex, and nationality were not significantly related to coronavirus patients' psychological health problems. Assessments and interventions for psychosocial concerns, integration of mental health considerations, and treatment for severe psychosocial consequences must be administered in COVID-19 care facilities.