Leveraging electronic health records and knowledge networks for Alzheimer's disease prediction and sex-specific biological insights.

Identification of Alzheimer's disease (AD) onset risk can facilitate interventions before irreversible disease progression. We demonstrate that electronic health records from the University of California, San Francisco, followed by knowledge networks (for example, SPOKE) allow for (1) prediction of AD onset and (2) prioritization of biological hypotheses, and (3) contextualization of sex dimorphism. We trained random forest models and predicted AD onset on a cohort of 749 individuals with AD and 250,545 controls with a mean area under the receiver operating characteristic of 0.

Evaluation of Commercially Available Machine Interpretation Applications for Simple Clinical Communication.

Background: Accessing professional medical interpreters for brief, low risk exchanges can be challenging. Machine translation (MT) for verbal communication has the potential to be a useful clinical tool, but few evaluations exist.

Objective: We evaluated the quality of three MT applications for English-Spanish and English-Mandarin two-way interpretation of low complexity brief clinical communication compared with human interpretation.

Reversal of cancer gene expression identifies repurposed drugs for diffuse intrinsic pontine glioma.

Diffuse intrinsic pontine glioma (DIPG) is an aggressive incurable brainstem tumor that targets young children. Complete resection is not possible, and chemotherapy and radiotherapy are currently only palliative. This study aimed to identify potential therapeutic agents using a computational pipeline to perform an in silico screen for novel drugs.

The Impact of the COVID-19 Pandemic on Internet Use and the Use of Digital Health Tools: Secondary Analysis of the 2020 Health Information National Trends Survey.

Background: The COVID-19 pandemic increased the use of digital tools in health care (eg, patient portal, telemedicine, and web-based scheduling). Studies have shown that older individuals, racial/ethnic minority groups, or populations with lower educational attainment or income have lower rates of using digital health tools. Digitalization of health care may exacerbate already existing access barriers in these populations.

Satisfaction can co-exist with hesitation: qualitative analysis of acceptability of telemedicine among multi-lingual patients in a safety-net healthcare system during the COVID-19 pandemic.

Background: The COVID-19 pandemic triggered unprecedented expansion of outpatient telemedicine in the United States in all types of health systems, including safety-net health systems. These systems generally serve low-income, racially/ethnically/linguistically diverse patients, many of whom face barriers to digital health access. These patients' perspectives are vital to inform ongoing, equitable implementation efforts.

Standardized Integration of Person-Generated Data Into Routine Clinical Care.

Person-generated data (PGD) are a valuable source of information on a person's health state in daily life and in between clinic visits. To fully extract value from PGD, health care organizations must be able to smoothly integrate data from PGD devices into routine clinical workflows. Ideally, to enhance efficiency and flexibility, such integrations should follow reusable processes that can easily be replicated for multiple devices and data types.

Deep phenotyping of Alzheimer's disease leveraging electronic medical records identifies sex-specific clinical associations.

Alzheimer's Disease (AD) is a neurodegenerative disorder that is still not fully understood. Sex modifies AD vulnerability, but the reasons for this are largely unknown. We utilize two independent electronic medical record (EMR) systems across 44,288 patients to perform deep clinical phenotyping and network analysis to gain insight into clinical characteristics and sex-specific clinical associations in AD.

OCTAD: an open workspace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features.

As the field of precision medicine progresses, treatments for patients with cancer are starting to be tailored to their molecular as well as their clinical features. The emerging cancer subtypes defined by these molecular features require that dedicated resources be used to assist the discovery of drug candidates for preclinical evaluation. Voluminous gene expression profiles of patients with cancer have been accumulated in public databases, enabling the creation of cancer-specific expression signatures.

Hippo Cascade Controls Lineage Commitment of Liver Tumors in Mice and Humans.

Primary liver cancer consists mainly of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). A subset of human HCCs expresses a ICC-like gene signature and is classified as ICC-like HCC. The Hippo pathway is a critical regulator of normal and malignant liver development.