Publications by authors named "Si-Eun Lee"

CNS Drug discovery has been challenging due to the lack of clarity on CNS diseases' basic biological and pathological mechanisms. Despite the difficulty, some CNS drugs have been developed based on phenotypic effects. Herein, we propose a phenotype-structure relationship model, which predicts an anti-neuroinflammatory potency based on 3D molecular structures of the phenotype-active or inactive compounds without specifying targets.

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Purpose: To explore the abnormality score trends of artificial intelligence-based computer-aided diagnosis (AI-CAD) in the serial mammography of patients until a final diagnosis of breast cancer.

Method: From 2015 to 2019, 126 breast cancer patients who had at least two previous mammograms obtained from 2008 up to cancer diagnosis were included. AI-CAD was retrospectively applied to 487 previous mammograms and all the abnormality scores calculated by AI-CAD were obtained.

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Article Synopsis
  • Data-driven digital learning and AI-CAD can enhance the diagnostic skills of novice students in identifying thyroid nodules.
  • A study involving 26 inexperienced readers showed significant improvement in diagnostic performance after they participated in an online learning session and utilized AI assistance.
  • While self-learning benefitted radiology residents, it did not equally aid readers from other specialties, highlighting the importance of prior knowledge in ultrasonography for effective learning.
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Objective: Artificial intelligence-based computer-aided diagnosis (AI-CAD) is increasingly used in mammography. While the continuous scores of AI-CAD have been related to malignancy risk, the understanding of how to interpret and apply these scores remains limited. We investigated the positive predictive values (PPVs) of the abnormality scores generated by a deep learning-based commercial AI-CAD system and analyzed them in relation to clinical and radiological findings.

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Article Synopsis
  • Enavogliflozin (0.3 mg) is a new SGLT-2 inhibitor evaluated for its effectiveness and safety in type 2 diabetes patients, specifically focusing on kidney function in two 24-week trials involving 470 participants.
  • Results showed enavogliflozin significantly reduced HbA1c and fasting plasma glucose levels more than dapagliflozin, especially in those with mildly reduced kidney function, while maintaining effectiveness regardless of renal status.
  • The study concludes that enavogliflozin offers superior glucose-lowering effects compared to dapagliflozin, making it a promising option for patients struggling with glycemic control.
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Purpose: To evaluate artificial intelligence-based computer-aided diagnosis (AI-CAD) for screening mammography, we analyzed the diagnostic performance of radiologists by providing and withholding AI-CAD results alternatively every month.

Methods: This retrospective study was approved by the institutional review board with a waiver for informed consent. Between August 2020 and May 2022, 1819 consecutive women (mean age 50.

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Mammography is currently the most commonly used modality for breast cancer screening. However, its sensitivity is relatively low in women with dense breasts. Dense breast tissues show a relatively high rate of interval cancers and are at high risk for developing breast cancer.

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Screening mammography has decreased performance in patients with dense breasts. Supplementary screening ultrasound is a recommended option in such patients, although it has yielded mixed results in prior investigations. The purpose of this article is to compare the performance characteristics of screening mammography alone, standalone artificial intelligence (AI), ultrasound alone, and mammography in combination with AI and/or ultrasound in patients with dense breasts.

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Purpose: To evaluate the stand-alone diagnostic performances of AI-CAD and outcomes of AI-CAD detected abnormalities when applied to the mammographic interpretation workflow.

Methods: From January 2016 to December 2017, 6499 screening mammograms of 5228 women were collected from a single screening facility. Historic reads of three radiologists were used as radiologist interpretation.

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To evaluate the consistency in the performance of Artificial Intelligence (AI)-based diagnostic support software in short-term digital mammography reimaging after core needle biopsy. Of 276 women who underwent short-term (<3 mo) serial digital mammograms followed by breast cancer surgery from Jan. to Dec.

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Objective: This study aimed to evaluate employees' attitudes toward cancer, patients with cancer, and cancer survivors' return to work.

Methods: This study used a cross-sectional survey with online questionnaires to collect data during a 1-month period in April 2022. A stratified sampling method was used to select 237 participants.

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Article Synopsis
  • This study compared the effectiveness and safety of enavogliflozin and dapagliflozin in Korean patients with type 2 diabetes who were not adequately controlled by metformin and gemigliptin.
  • In a randomized, double-blind trial, patients were given either enavogliflozin (0.3 mg/day) or dapagliflozin (10 mg/day) for 24 weeks, measuring changes in HbA1c as the primary outcome.
  • Both medications effectively reduced HbA1c levels with similar overall effectiveness and safety profiles, but enavogliflozin resulted in a greater increase in urine glucose-creatinine ratio compared to dapagliflozin.
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Cosmetics, especially rinse-off personal care products (PCPs), such as shampoo, facial cleanser, and body wash, are composed of various chemicals and are one of the sources of chemicals released into aquatic ecosystems. Therefore, the cosmetic industry strives to reduce the impact of their products on the aquatic environment. In this study, we proposed an algorithm based on persistence, bioaccumulation potential, and toxicity (PBT) for the environmental risk assessment of cosmetics.

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Background: Mammography yields inevitable recall for indeterminate findings that need to be confirmed with additional views.

Purpose: To explore whether the artificial intelligence (AI) algorithm for mammography can reduce false-positive recall in patients who undergo the spot compression view.

Material And Methods: From January to December 2017, 236 breasts from 225 women who underwent the spot compression view due to focal asymmetry, mass, or architectural distortion on standard digital mammography were included.

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Virtual screening has significantly improved the success rate of early stage drug discovery. Recent virtual screening methods have improved owing to advances in machine learning and chemical information. Among these advances, the creative extraction of drug features is important for predicting drug-target interaction (DTI), which is a large-scale virtual screening of known drugs.

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As thyroid and breast cancer have several US findings in common, we applied an artificial intelligence computer-assisted diagnosis (AI-CAD) software originally developed for thyroid nodules to breast lesions on ultrasound (US) and evaluated its diagnostic performance. From January 2017 to December 2017, 1042 breast lesions (mean size 20.2 ± 11.

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Article Synopsis
  • A study looked at how using artificial intelligence (AI) can help doctors, called radiologists, better read ultrasound images of breast lumps.
  • They tested this with 492 images, where some lumps were cancerous and others were not, and had both new and experienced radiologists check the images.
  • The results showed that using AI made the doctors much better at finding out if lumps were cancer or not, especially when they looked at images all at once instead of one after the other.
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Objective: To evaluate how breast cancers are depicted by artificial intelligence-based computer-assisted diagnosis (AI-CAD) according to clinical, radiological, and pathological factors.

Materials And Methods: From January 2017 to December 2017, 896 patients diagnosed with 930 breast cancers were enrolled in this retrospective study. Commercial AI-CAD was applied to digital mammograms and abnormality scores were obtained.

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Objectives: To investigate the malignancy rate of probably benign calcifications assessed by digital magnification view and imaging and clinical features associated with malignancy.

Methods: This retrospective study included consecutive women with digital magnification views assessed as probably benign for calcifications without other associated mammographic findings from March 2009 to January 2014. Initial studies rendering a probably benign assessment were analyzed, with biopsy or 4-year imaging follow-up.

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Background Low nuclear grade ductal carcinoma in situ (DCIS) identified at biopsy can be upgraded to intermediate to high nuclear grade DCIS at surgery. Methods that confirm low nuclear grade are needed to consider nonsurgical approaches for these patients. Purpose To develop a preoperative model to identify low nuclear grade DCIS and to evaluate factors associated with low nuclear grade DCIS at biopsy that was not upgraded to intermediate to high nuclear grade DCIS at surgery.

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We evaluated and compared the mammographic density assessment of an artificial intelligence-based computer-assisted diagnosis (AI-CAD) program using inter-rater agreements between radiologists and an automated density assessment program. Between March and May 2020, 488 consecutive mammograms of 488 patients (56.2 ± 10.

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