What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
His primary areas of investigation include Mammography, Artificial intelligence, Artificial neural network, Radiology and Receiver operating characteristic.
His research on Mammography focuses in particular on Breast imaging.
His Artificial intelligence research includes themes of Digital mammography and Computer vision.
His Artificial neural network study is focused on Machine learning in general.
His work carried out in the field of Radiology brings together such families of science as Prostate cancer and Retrospective cohort study.
His research in Receiver operating characteristic focuses on subjects like Breast cancer, which are connected to Patient age and Medical history.
His most cited work include:
- 2008 Special Issue: Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance (410 citations)
- Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance (348 citations)
- Breast cancer: prediction with artificial neural network based on BI-RADS standardized lexicon. (194 citations)
What are the main themes of his work throughout his whole career to date?
Joseph Y. Lo mainly investigates Mammography, Artificial intelligence, Breast cancer, Imaging phantom and Tomosynthesis.
His biological study spans a wide range of topics, including Computer-aided diagnosis, Radiology and Nuclear medicine.
His study focuses on the intersection of Radiology and fields such as Receiver operating characteristic with connections in the field of Data set.
The concepts of his Artificial intelligence study are interwoven with issues in Machine learning, Computer vision and Pattern recognition.
In Breast cancer, Joseph Y. Lo works on issues like Biopsy, which are connected to Breast biopsy.
His Tomosynthesis study also includes
- Digital Tomosynthesis Mammography that connect with fields like Medical imaging,
- Medical physics that intertwine with fields like Radiation treatment planning and Dosimetry.
He most often published in these fields:
- Mammography (47.55%)
- Artificial intelligence (44.91%)
- Breast cancer (23.02%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (44.91%)
- Pattern recognition (15.85%)
- Mammography (47.55%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Mammography, Imaging phantom and Biomedical engineering.
Joseph Y. Lo interconnects Computer vision, Digital mammography and Receiver operating characteristic in the investigation of issues within Artificial intelligence.
His Pattern recognition study combines topics from a wide range of disciplines, such as Field, Autoencoder and Computed tomography.
His Mammography study necessitates a more in-depth grasp of Breast cancer.
His Imaging phantom research integrates issues from Image quality, Iterative reconstruction and Digital Breast Tomosynthesis.
Within one scientific family, Joseph Y. Lo focuses on topics pertaining to Watchful waiting under Machine learning, and may sometimes address concerns connected to Artificial neural network.
Between 2017 and 2021, his most popular works were:
- Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms (43 citations)
- Prediction of Occult Invasive Disease in Ductal Carcinoma in Situ Using Deep Learning Features (37 citations)
- Anomaly detection for medical images based on a one-class classification (20 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Joseph Y. Lo focuses on Artificial intelligence, Breast cancer, Digital mammography, Convolutional neural network and Receiver operating characteristic.
In his study, which falls under the umbrella issue of Artificial intelligence, Autoencoder, Medical diagnosis and Artificial neural network is strongly linked to Pattern recognition.
His Digital Breast Tomosynthesis and Mammography study in the realm of Breast cancer interacts with subjects such as In situ.
His work on Screening mammography is typically connected to Validation cohort as part of general Mammography study, connecting several disciplines of science.
His research in Digital mammography intersects with topics in Medical physics and Anthropomorphic phantom.
The Receiver operating characteristic study combines topics in areas such as Imaging modalities, Radiology and Computed tomography.
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