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- research-articleSeptember 2024
Optimizing trigger timing in minimal ovarian stimulation for In Vitro fertilization using machine learning models with random search hyperparameter tuning
- Nayeli Areli Pérez-Padilla,
- Rodolfo Garcia-Sanchez,
- Omar Avalos,
- Jorge Gálvez,
- Minglei Bian,
- Liang Yu,
- Yimin Shu,
- Ming Feng,
- Frank D. Yelian
Computers in Biology and Medicine (CBIM), Volume 179, Issue Chttps://doi.org/10.1016/j.compbiomed.2024.108856AbstractVarious studies have emphasized the importance of identifying the optimal Trigger Timing (TT) for the trigger shot in In Vitro Fertilization (IVF), which is crucial for the successful maturation and release of oocytes, especially in minimal ...
Highlights- AI-optimized trigger timing significantly increases the number of useable blastocysts.
- Oocyte quality and quantity are crucial for successful blastocyst formation.
- Hyperparameter optimization in ANN model significantly improves ...
- ArticleJune 2024
Image Processing and Deep Learning Methods for the Semantic Segmentation of Blastocyst Structures
AbstractEmbryo selection is an indispensable step to ensure the success of in vitro fertilization. There are two techniques to perform embryo selection: preimplantation genetic screening and embryo morphological grading. However, even with these ...
- research-articleMarch 2024
A clinical consensus-compliant deep learning approach to quantitatively evaluate human in vitro fertilization early embryonic development with optical microscope images
- Zaowen Liao,
- Chaoyu Yan,
- Jianbo Wang,
- Ningfeng Zhang,
- Huan Yang,
- Chenghao Lin,
- Haiyue Zhang,
- Wenjun Wang,
- Weizhong Li
Artificial Intelligence in Medicine (AIIM), Volume 149, Issue Chttps://doi.org/10.1016/j.artmed.2024.102773AbstractThe selection of embryos is a key for the success of in vitro fertilization (IVF). However, automatic quality assessment on human IVF embryos with optical microscope images is still challenging. In this study, we developed a clinical consensus-...
Highlights- Esava is a clinic-compliant deep learning approach for IVF embryonic evaluation.
- Esava assesses blastomeres' number and uniformity, and identifies their borders.
- The novel Crowd-NMS algorithm enhances the object detection and ...
- research-articleOctober 2023
Comparing cost sensitive classifiers by the false-positive to false- negative ratio in diagnostic studies
Expert Systems with Applications: An International Journal (EXWA), Volume 227, Issue Chttps://doi.org/10.1016/j.eswa.2023.120303AbstractNowadays researchers want to be cautious about cost of building models which can generate false positives and false negatives in unexpected ways. They keep on searching for various measures for controlling such behavior depending upon ...
- research-articleJuly 2021
The Association between Baseline Serum SHBG and the Number of Retrieved Oocytes in Chinese Infertile Patients Undergoing IVF Treatment of PPOS Protocol: A Restrospective Cohort Study
BIBE2021: The Fifth International Conference on Biological Information and Biomedical EngineeringArticle No.: 30, Pages 1–5https://doi.org/10.1145/3469678.3469708This study aimed to investigate the association between the baseline circulating sex hormone binding globulin (SHBG) concentration and the number of oocytes retrieved. This retrospective cohort study included 1477 patients who underwent PPOS treatment ...
- research-articleApril 2021
Automated cell division classification in early mouse and human embryos using convolutional neural networks
Neural Computing and Applications (NCAA), Volume 33, Issue 7Pages 2217–2228https://doi.org/10.1007/s00521-020-05127-8AbstractDuring in vitro fertilization (IVF), the timing of cell divisions in early human embryos is a key predictor of embryo viability. Recent developments in time-lapse microscopy (TLM) have allowed us to observe cell divisions in much greater detail ...
- ArticleOctober 2019
Joint Optimization of Convolutional Neural Network and Image Preprocessing Selection for Embryo Grade Prediction in In Vitro Fertilization
- Kento Uchida,
- Shota Saito,
- Panca Dewi Pamungkasari,
- Yusei Kawai,
- Ita Fauzia Hanoum,
- Filbert H. Juwono,
- Shinichi Shirakawa
AbstractThe convolutional neural network (CNN) is a standard tool for image recognition. To improve the performance of CNNs, it is important to design not only the network architecture but also the preprocessing of the input image. Extracting or enhancing ...
- articleApril 2011
Integrating genetic algorithm and decision tree learning for assistance in predicting in vitro fertilization outcomes
Expert Systems with Applications: An International Journal (EXWA), Volume 38, Issue 4Pages 4437–4449https://doi.org/10.1016/j.eswa.2010.09.112Accurate and early prediction of the outcome of an in vitro fertilization (IVF) treatment is important for both patients and physicians. The most common question asked by IVF patients is ''What are my chances of conceiving?'' The answer to this ...