Abstract: In generating training and testing datasets for machine learning, manual annotation of a large volume of data is impractical and expensive. A machine-learning model for detecting carcinoma (CA) from a whole slide image (WSI) processes average cellular features of cells identified on the WSI. Each cellular feature is a descriptive statistic of the cells, advantageously allowing the training and testing datasets to be constructed without a costly annotation process of pixelwise labelling each cell on a WSI training sample. Apart from predicting a CA case or a non-CA case for the WSI, the machine-learning model is also usable to: identify a suspicious CA case for priority assessment if a non-CA case is predicted for the WSI; generate a tumor probability heatmap of the WSI for visualizing potential CA regions on the WSI to assist pathological assessment; and assess quality control of a triage system before implementation in clinical setting.

Abstract: This disclosure pertains to methods of treating prostate cancer in a subject, including prostate cancer comprising at least one somatic AR tumor mutation, such as metastatic prostate cancer, castrate-resistant prostate cancer, metastatic castrate-resistant prostate cancer, progressive metastatic castrate-resistant prostate cancer, castrate-sensitive prostate cancer, metastatic castrate-sensitive prostate cancer, prostate cancer naïve to novel hormonal agents (NHAs), metastatic prostate cancer naïve NHAs, castrate-resistant prostate cancer naïve to NHAs, castrate-sensitive prostate cancer naïve to NHAs, metastatic castrate-resistant prostate cancer naïve to NHAs, and metastatic castrate-sensitive prostate cancer naïve to NHAs, wherein the method comprises administering to a subject in need thereof a therapeutically effective amount of Compound A, or a pharmaceutically acceptable salt thereof.

Abstract: The subject invention pertains to methods and systems for the quantification of clonality between tissue samples obtained from a subject having or suspected to have cancer and treatment of the subject tailored to the origin of tumors in the tissue samples as primary cancer or metastases based on the clonality quantification.

Abstract: Systems and methods for use in evaluating a position of a satellite dish are provided. One system includes an antenna configured to receive an input satellite signal at a current position of a satellite dish and automatic gain control circuitry configured to apply a variable gain to the input satellite signal to produce a modified signal at a desired level. The system further includes power control circuitry configured to generate an output signal using the modified signal. The power control circuitry is configured to adjust a power level of the output signal using the variable gain applied to the input satellite signal such that the output signal is proportional to the input signal.