Abstract: A method of assessing a likelihood of a patient having a pulmonary embolism (PE) comprises receiving discrete patient data, including patient-related clinical and demographic data pertinent to the patient, receiving electrocardiograph (ECG) waveform data obtained from examination of the patient, processing both the received discrete patient data and received set of ECG waveform data using a supervised deep learning multimodal fusion model that has been trained using analogous input training data including both discrete patient data and ECG waveform data to obtain an optimal match to results from corresponding patient computed tomography pulmonary angiograms (CTPA), indicative of a presence or absence of a pulmonary embolism, and outputting a measure of the likelihood of the patient having a pulmonary embolism.

Abstract: An example method of diagnosing chronic kidney disease (CKD) includes obtaining an electronic medical record for a patient having medical data. The medical data includes an indication if the patient had been previously diagnosed with CKD, an indication if the patient had previously undergone a kidney transplant, an indication if the patient had previously undergone a renal dialysis procedure, an indication if the patient had previously been diagnosed with another type of kidney disease, one or more glomerular filtration rate (GFR) measurements associated with the patient, an indication if the patient has type 2 diabetes, and/or an indication if the patient has hypertension. The method also includes automatically determining that the patient has CKD or does not have CKD based on the medical data in the electronic record.

Abstract: An example method of diagnosing chronic kidney disease (CKD) includes obtaining an electronic medical record for a patient having medical data. The medical data includes an indication if the patient had been previously diagnosed with CKD, an indication if the patient had previously undergone a kidney transplant, an indication if the patient had previously undergone a renal dialysis procedure, an indication if the patient had previously been diagnosed with another type of kidney disease, one or more glomerular filtration rate (GFR) measurements associated with the patient, an indication if the patient has type 2 diabetes, and/or an indication if the patient has hypertension. The method also includes automatically determining that the patient has CKD or does not have CKD based on the medical data in the electronic record.

Abstract: Methods, computer systems, and computer-readable storage media for maximizing information associated with content items on a search engine results page are provided. A total number of pixels available on the search engine results page is determined, and content items are received in response to a search query. Templates are selected from a set of pre-generated templates, and the content items are initially assigned to the templates such that a number of content items is maximized on the search engine results page. Next, and starting with the highest-ranked content item, an optimal size is determined for each of the templates such that the content-item-per-pixel is maximized within each template. After resizing the templates to the optimal size, the content items are presented on the search engine results page.

Abstract: An example method of automated medical diagnosis includes obtaining an electronic longitudinal data set for each of a plurality of patients, where each data set includes a plurality of measurement values corresponding to a metric, where each measurement value is associated with a respective time point. The method also includes arranging the data sets into two or more clusters. Arranging the data sets includes aligning the data sets according to their respective time points, selecting a cluster center for each cluster, determining a similarity between each data set and each cluster center, assigning each data set to a particular cluster based on the similarities, and iteratively re-aligning one or more of the data sets and/or reselecting one or more cluster centers, determining an updated similarity between each data set and each cluster center, and re-assigning data sets to particular clusters based on the updated similarities until a stop criterion is met.

Abstract: An example method of diagnosing chronic kidney disease (CKD) includes obtaining an electronic medical record for a patient having medical data. The medical data includes an indication if the patient had been previously diagnosed with CKD, an indication if the patient had previously undergone a kidney transplant, an indication if the patient had previously undergone a renal dialysis procedure, an indication if the patient had previously been diagnosed with another type of kidney disease, one or more glomerular filtration rate (GFR) measurements associated with the patient, an indication if the patient has type 2 diabetes, and/or an indication if the patient has hypertension. The method also includes automatically determining that the patient has CKD or does not have CKD based on the medical data in the electronic record.

Abstract: Methods, computer systems, and computer-readable storage media for maximizing information associated with content items on a search engine results page are provided. A total number of pixels available on the search engine results page is determined, and content items are received in response to a search query. Templates are selected from a set of pre-generated templates, and the content items are initially assigned to the templates such that a number of content items is maximized on the search engine results page. Next, and starting with the highest-ranked content item, an optimal size is determined for each of the templates such that the content-item-per-pixel is maximized within each template. After resizing the templates to the optimal size, the content items are presented on the search engine results page.

Abstract: Methods, computer systems, and computer-readable storage media for maximizing information associated with content items on a search engine results page are provided. A total number of pixels available on the search engine results page is determined, and content items are received in response to a search query. Templates are selected from a set of pre-generated templates, and the content items are initially assigned to the templates such that a number of content items is maximized on the search engine results page. Next, and starting with the highest-ranked content item, an optimal size is determined for each of the templates such that the content-item-per-pixel is maximized within each template. After resizing the templates to the optimal size, the content items are presented on the search engine results page.

Abstract: Methods, computer systems, and computer-readable storage media for maximizing information associated with content items on a search engine results page are provided. A total number of pixels available on the search engine results page is determined, and content items are received in response to a search query. Templates are selected from a set of pre-generated templates, and the content items are initially assigned to the templates such that a number of content items is maximized on the search engine results page. Next, and starting with the highest-ranked content item, an optimal size is determined for each of the templates such that the content-item-per-pixel is maximized within each template. After resizing the templates to the optimal size, the content items are presented on the search engine results page.