Abstract: The present invention provides methods for the assessment of an adnexal mass predetermined to be benign or asymptomatic (e.g., asymptomatic or benign adnexal mass) in a variety of subjects (e.g., pre- and post-menopausal women). In particular, the present invention provides methods for determining the malignancy risk of ovarian tumors in selected subjects (e.g., benign or indeterminate risk).

Abstract: Disclosed here are Generative Adversarial Network (GANs) based data augmentation methods for providing synthetic biological samples, such as urine or blood samples, in scenarios with a small imbalanced biomedical dataset for machine learning systems. In specific aspects, the disclosure provides synthetic data generated from a learned distribution of urinary analyte concentrations from real samples with corresponding biomarker data, particularly cfDNA.

Abstract: Methods are provided to improve the positive predictive value for cancer detection using cell-free nucleic acid samples. The methods can include the use of at least two assays. The assays can vary, for example, with respect to sensitivity, specificity, sequencing depth, analyte, and cost. An exemplary method can be used to provide an initial cancer assay with high sensitivity and a follow-up assay with high specificity in detecting cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel for diagnosis of cancer.

Abstract: A method for performing data structuring on unstructured medical data and generating healthcare insights. The method may include receiving the unstructured medical data pertaining to at least one patient and at least one physician; transforming the received unstructured medical data into structured data using a data-centric artificial intelligence (DCAI); labeling the structured data and performing hidden structure discovery to establish data equivalence of the labeled data; and providing the hidden structure discovered data as input to a model-centric artificial intelligence (MCAI) engine to generate the healthcare insights.

Abstract: In some embodiments, the disclosure relates generally to compositions, comprising a single reaction mixture containing a plurality of different populations of discrete supports, and a plurality of different populations of target nucleic acids. The single reaction mixture can contain a first population of beads; a second population of beads; a first population of target nucleic acids, where at least two different target nucleic acids in the first population of target nucleic acids can bind to a bead in the first population of beads; and a second population of target nucleic acids, where at least two different target nucleic acids in the second population of target nucleic acids can bind to a bead in the second population of beads. The single reaction mixture can be employed to monoclonally amplify the first target nucleic acids on the first beads, and monoclonally amplify the second target nucleic acids on the second beads.

Abstract: Methods of identifying changes in genomic DNA copy number are disclosed. This disclosure provides methods for detecting chromosomal aberrations in a subject using Hidden Markov modeling. In some cases, methods provided herein use de novo sequence assembly to detect chromosomal aberrations in a subject. The methods can be used to detect copy number changes in cancerous tissue compared to normal tissue. The methods can be used to diagnose cancer and other diseases associated with chromosomal anomalies.

Abstract: In some embodiments, the disclosure relates generally to compositions, comprising a single reaction mixture containing a plurality of different populations of discrete supports, and a plurality of different populations of target nucleic acids. The single reaction mixture can contain a first population of beads; a second population of beads; a first population of target nucleic acids, where at least two different target nucleic acids in the first population of target nucleic acids can bind to a bead in the first population of beads; and a second population of target nucleic acids, where at least two different target nucleic acids in the second population of target nucleic acids can bind to a bead in the second population of beads. The single reaction mixture can be employed to monoclonally amplify the first target nucleic acids on the first beads, and monoclonally amplify the second target nucleic acids on the second beads.

Abstract: Methods of identifying changes in genomic DNA copy number are disclosed. This disclosure provides methods for detecting chromosomal aberrations in a subject using Hidden Markov modeling. In some cases, methods provided herein use de novo sequence assembly to detect chromosomal aberrations in a subject. The methods can be used to detect copy number changes in cancerous tissue compared to normal tissue. The methods can be used to diagnose cancer and other diseases associated with chromosomal anomalies.

Abstract: Methods for estimating genomic copy number and loss of heterozygosity using Hidden Markov Model based estimation are disclosed.

Abstract: Methods are provided to improve the positive predictive value for cancer detection using cell-free nucleic acid samples. The methods can include the use of at least two assays. The assays can vary, for example, with respect to sensitivity, specificity, sequencing depth, analyte, and cost. An exemplary method can be used to provide an initial cancer assay with high sensitivity and a follow-up assay with high specificity in detecting cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel for diagnosis of cancer.

Abstract: The present description provides a cancer assay panel for targeted detection of cancer-specific methylation patterns. Further provided herein includes methods of designing, making, and using the cancer assay panel for diagnosis of cancer.

Abstract: In some embodiments, the disclosure relates generally to compositions, comprising a single reaction mixture containing a plurality of different populations of discrete supports, and a plurality of different populations of target nucleic acids. The single reaction mixture can contain a first population of beads; a second population of beads; a first population of target nucleic acids, where at least two different target nucleic acids in the first population of target nucleic acids can bind to a bead in the first population of beads; and a second population of target nucleic acids, where at least two different target nucleic acids in the second population of target nucleic acids can bind to a bead in the second population of beads. The single reaction mixture can be employed to monoclonally amplify the first target nucleic acids on the first beads, and monoclonally amplify the second target nucleic acids on the second beads.

Abstract: Methods for estimating genomic copy number and loss of heterozygosity using Hidden Markov Model based estimation are disclosed.

Abstract: Methods of identifying changes in genomic DNA copy number are disclosed. This disclosure provides methods for detecting chromosomal aberrations in a subject using Hidden Markov modeling. In some cases, methods provided herein use de novo sequence assembly to detect chromosomal aberrations in a subject. The methods can be used to detect copy number changes in cancerous tissue compared to normal tissue. The methods can be used to diagnose cancer and other diseases associated with chromosomal anomalies.

Abstract: Methods for estimating genomic copy number and loss of heterozygosity using Hidden Markov Model based estimation are disclosed.

Abstract: In some embodiments, the disclosure relates generally to compositions, comprising a single reaction mixture containing a plurality of different populations of discrete supports, and a plurality of different populations of target nucleic acids. The single reaction mixture can contain a first population of beads; a second population of beads; a first population of target nucleic acids, where at least two different target nucleic acids in the first population of target nucleic acids can bind to a bead in the first population of beads; and a second population of target nucleic acids, where at least two different target nucleic acids in the second population of target nucleic acids can bind to a bead in the second population of beads. The single reaction mixture can be employed to monoclonally amplify the first target nucleic acids on the first beads, and monoclonally amplify the second target nucleic acids on the second beads.

Abstract: Methods for estimating genomic copy number and loss of heterozygosity using Hidden Markov Model based estimation are disclosed.

Abstract: Biopolymeric array scanners that are capable of automatically selecting a dye specific scale factor to employ for a plurality of different dyes, as wells as methods for making and using the same, are provided. In many embodiments, the actual dye specific scale factor automatically selected by the scanner is one that is equal to a preset “master” scale factor, so that the scanner reads any supported dye using the same constant scale factor. The dye specific scale factor selection is typically made by reference to a collection of nominal scale factors for each member of the plurality of dyes. In using the subject scanners, a user simply inputs the one or more dyes being used in a given array assay, and the scanner automatically reads the array using an automatically chosen dye specific scale factor for the selected dyes. Also provided are methods of obtaining collections of nominal scale factors and computer readable mediums comprising the same.