Morbid obesity requires active intervention, with treatment options including lifestyle modification, pharmacotherapy, and surgery. As the prevalence of obesity continues to rise in Korea, it is crucial for specialists and general practitioners to have a comprehensive understanding of obesity and its management. Bariatric surgery is the most effective treatment modality for obesity, leading to significant weight loss and metabolic benefits. It involves surgical alterations of normal anatomical structures to improve overall health. Therefore, selecting the appropriate procedure based on the individual characteristics of patients is crucial. This review highlights the two most commonly performed bariatric procedures worldwide, including in Korea: sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB). Furthermore, it provides a comprehensive overview of the surgical techniques involved in SG and RYGB, addresses potential complications, and presents findings from key studies on the weight loss and metabolic outcomes of these surgeries. Additionally, to support clinical application, the review provides outcome data for these procedures based on studies conducted in Korean populations. In addition to SG and RYGB, this review briefly introduces other surgical and endoscopic options, as well as pharmacological treatments that are currently available or may become viable options in the near future.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

Morbid obesity requires active intervention, with treatment options including lifestyle modification, pharmacotherapy, and surgery. As the prevalence of obesity continues to rise in Korea, it is crucial for specialists and general practitioners to have a comprehensive understanding of obesity and its management. Bariatric surgery is the most effective treatment modality for obesity, leading to significant weight loss and metabolic benefits. It involves surgical alterations of normal anatomical structures to improve overall health. Therefore, selecting the appropriate procedure based on the individual characteristics of patients is crucial. This review highlights the two most commonly performed bariatric procedures worldwide, including in Korea: sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB). Furthermore, it provides a comprehensive overview of the surgical techniques involved in SG and RYGB, addresses potential complications, and presents findings from key studies on the weight loss and metabolic outcomes of these surgeries. Additionally, to support clinical application, the review provides outcome data for these procedures based on studies conducted in Korean populations. In addition to SG and RYGB, this review briefly introduces other surgical and endoscopic options, as well as pharmacological treatments that are currently available or may become viable options in the near future.

Morbid obesity requires active intervention, with treatment options including lifestyle modification, pharmacotherapy, and surgery. As the prevalence of obesity continues to rise in Korea, it is crucial for specialists and general practitioners to have a comprehensive understanding of obesity and its management. Bariatric surgery is the most effective treatment modality for obesity, leading to significant weight loss and metabolic benefits. It involves surgical alterations of normal anatomical structures to improve overall health. Therefore, selecting the appropriate procedure based on the individual characteristics of patients is crucial. This review highlights the two most commonly performed bariatric procedures worldwide, including in Korea: sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB). Furthermore, it provides a comprehensive overview of the surgical techniques involved in SG and RYGB, addresses potential complications, and presents findings from key studies on the weight loss and metabolic outcomes of these surgeries. Additionally, to support clinical application, the review provides outcome data for these procedures based on studies conducted in Korean populations. In addition to SG and RYGB, this review briefly introduces other surgical and endoscopic options, as well as pharmacological treatments that are currently available or may become viable options in the near future.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

Morbid obesity requires active intervention, with treatment options including lifestyle modification, pharmacotherapy, and surgery. As the prevalence of obesity continues to rise in Korea, it is crucial for specialists and general practitioners to have a comprehensive understanding of obesity and its management. Bariatric surgery is the most effective treatment modality for obesity, leading to significant weight loss and metabolic benefits. It involves surgical alterations of normal anatomical structures to improve overall health. Therefore, selecting the appropriate procedure based on the individual characteristics of patients is crucial. This review highlights the two most commonly performed bariatric procedures worldwide, including in Korea: sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB). Furthermore, it provides a comprehensive overview of the surgical techniques involved in SG and RYGB, addresses potential complications, and presents findings from key studies on the weight loss and metabolic outcomes of these surgeries. Additionally, to support clinical application, the review provides outcome data for these procedures based on studies conducted in Korean populations. In addition to SG and RYGB, this review briefly introduces other surgical and endoscopic options, as well as pharmacological treatments that are currently available or may become viable options in the near future.

Purpose: The molecular classification of breast cancer is crucial for effective treatment. The emergence of digital pathology has ushered in a new era in which weakly supervised learning leveraging whole-slide images has gained prominence in developing deep learning models because this approach alleviates the need for extensive manual annotation. Weakly supervised learning was employed to classify the molecular subtypes of breast cancer. Materials and Methods: Our approach capitalizes on two whole-slide image datasets: one consisting of breast cancer cases from the Korea University Guro Hospital (KG) and the other originating from The Cancer Genomic Atlas dataset (TCGA). Furthermore, we visualized the inferred results using an attention-based heat map and reviewed the histomorphological features of the most attentive patches. Results: The KG+TCGA-trained model achieved an area under the receiver operating characteristics value of 0.749. An inherent challenge lies in the imbalance among subtypes. Additionally, discrepancies between the two datasets resulted in different molecular subtype proportions. To mitigate this imbalance, we merged the two datasets, and the resulting model exhibited improved performance. The attentive patches correlated well with widely recognized histomorphologic features. The triple-negative subtype has a high incidence of high-grade nuclei, tumor necrosis, and intratumoral tumor-infiltrating lymphocytes. The luminal A subtype showed a high incidence of collagen fibers. Conclusion The artificial intelligence (AI) model based on weakly supervised learning showed promising performance. A review of the most attentive patches provided insights into the predictions of the AI model. AI models can become invaluable screening tools that reduce costs and workloads in practice.

Morbid obesity requires active intervention, with treatment options including lifestyle modification, pharmacotherapy, and surgery. As the prevalence of obesity continues to rise in Korea, it is crucial for specialists and general practitioners to have a comprehensive understanding of obesity and its management. Bariatric surgery is the most effective treatment modality for obesity, leading to significant weight loss and metabolic benefits. It involves surgical alterations of normal anatomical structures to improve overall health. Therefore, selecting the appropriate procedure based on the individual characteristics of patients is crucial. This review highlights the two most commonly performed bariatric procedures worldwide, including in Korea: sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB). Furthermore, it provides a comprehensive overview of the surgical techniques involved in SG and RYGB, addresses potential complications, and presents findings from key studies on the weight loss and metabolic outcomes of these surgeries. Additionally, to support clinical application, the review provides outcome data for these procedures based on studies conducted in Korean populations. In addition to SG and RYGB, this review briefly introduces other surgical and endoscopic options, as well as pharmacological treatments that are currently available or may become viable options in the near future.

Background: Atherogenic dyslipidemia, which is frequently associated with type 2 diabetes (T2D) and insulin resistance, contributes to the development of vascular complications. Statin therapy is the primary approach to dyslipidemia management in T2D, however, the role of non-statin therapy remains unclear. Ezetimibe reduces cholesterol burden by inhibiting intestinal cholesterol absorption. Fibrates lower triglyceride levels and increase high-density lipoprotein cholesterol (HDL-C) levels via peroxisome proliferator- activated receptor alpha agonism. Therefore, when combined, these drugs effectively lower non-HDL-C levels. Despite this, few clinical trials have specifically targeted non-HDL-C, and the efficacy of triple combination therapies, including statins, ezetimibe, and fibrates, has yet to be determined. Methods: This is a multicenter, prospective, randomized, open-label, active-comparator controlled trial involving 3,958 eligible participants with T2D, cardiovascular risk factors, and elevated non-HDL-C (≥100 mg/dL). Participants, already on moderate-intensity statins, will be randomly assigned to either Ezefeno (ezetimibe/fenofibrate) addition or statin dose-escalation. The primary end point is the development of a composite of major adverse cardiovascular and diabetic microvascular events over 48 months. Conclusion This trial aims to assess whether combining statins, ezetimibe, and fenofibrate is as effective as, or possibly superior to, statin monotherapy intensification in lowering cardiovascular and microvascular disease risk for patients with T2D. This could propose a novel therapeutic approach for managing dyslipidemia in T2D.