Identifying and Reporting Dependent Adult abuse

Artificial Intelligence in Dermatology: A Primer.

Artificial intelligence is becoming increasingly important in dermatology, with studies reporting accuracy matching or exceeding dermatologists for the diagnosis of skin lesions from clinical and dermoscopic images. However, real-world clinical validation is currently lacking. We review dermatological applications of deep learning, the leading artificial intelligence technology for image analysis,...

Data science and machine learning in anesthesiology.

Machine learning (ML) is revolutionizing anesthesiology research. Unlike classical research methods that are largely inference-based, ML is geared more towards making accurate predictions. ML is a field of artificial intelligence concerned with developing algorithms and models to perform prediction tasks in the absence of explicit instructions. Most ML applications, despite being highly variable i...

Artificial intelligence versus clinicians: systematic review of design, reporting standards, and claims of deep learning studies.

OBJECTIVE: To systematically examine the design, reporting standards, risk of bias, and claims of studies comparing the performance of diagnostic deep...

Reporting quality of studies using machine learning models for medical diagnosis: a systematic review.

AIMS: We conducted a systematic review assessing the reporting quality of studies validating models based on machine learning (ML) for clinical diagno...

Machine learning and artificial intelligence research for patient benefit: 20 critical questions on transparency, replicability, ethics, and effectiveness.

Machine learning, artificial intelligence, and other modern statistical methods are providing new opportunities to operationalise previously untapped ...

Real-time tumor localization with single x-ray projection at arbitrary gantry angles using a convolutional neural network (CNN).

For tumor tracking therapy, precise knowledge of tumor position in real-time is very important. A technique using single x-ray projection based on a c...

Identification of the Species Constituents of Maggot Populations Feeding on Decomposing Remains-Facilitation of the Determination of Post Mortem Interval and Time Since Tissue Infestation through Application of Machine Learning and Direct Analysis in Real Time-Mass Spectrometry.

The utilization of entomological specimens such as larvae (maggots) for the estimation of time since oviposition (i.e., egg laying) for post mortem in...

Early detection of sepsis utilizing deep learning on electronic health record event sequences.

BACKGROUND: The timeliness of detection of a sepsis incidence in progress is a crucial factor in the outcome for the patient. Machine learning models ...

Evaluation of the predictive ability of ultrasound-based assessment of breast cancer using BI-RADS natural language reporting against commercial transcriptome-based tests.

PURPOSE: The objective of this study was to assess the classification capability of Breast Imaging Reporting and Data System (BI-RADS) ultrasound feat...

ADRENAL INSUFFICIENCY SECONDARY TO BILATERAL ADRENAL HEMORRHAGE ASSOCIATED WITH ANTIPHOSPHOLIPID SYNDROME.

OBJECTIVE: Antiphospholipid syndrome (APS) can involve multiple organ systems but endocrine manifestations are rare. In most cases adrenal insufficien...

Medication-rights detection using incident reports: A natural language processing and deep neural network approach.

Medication errors often occurred due to the breach of medication rights that are the right patient, the right drug, the right time, the right dose and...

Spatial Lifecourse Epidemiology Reporting Standards (ISLE-ReSt) statement.

Spatial lifecourse epidemiology is an interdisciplinary field that utilizes advanced spatial, location-based, and artificial intelligence technologies...

Can artificial intelligence help identify elder abuse and neglect?

A health care encounter is a potentially critical opportunity to detect elder abuse and initiate intervention. Unfortunately, health care providers cu...

Classification of Cancer at Prostate MRI: Deep Learning versus Clinical PI-RADS Assessment.

Background Men suspected of having clinically significant prostate cancer (sPC) increasingly undergo prostate MRI. The potential of deep learning to p...

Formalizing video documentation of the Critical View of Safety in laparoscopic cholecystectomy: a step towards artificial intelligence assistance to improve surgical safety.

BACKGROUND: In laparoscopic cholecystectomy (LC), achievement of the Critical View of Safety (CVS) is commonly advocated to prevent bile duct injuries...

Symmetry of generalized rivalry network models determines patterns of interocular grouping in four-location binocular rivalry.

Previously, symmetry of network models has been proposed to account for interocular grouping during binocular rivalry. Here, we construct and analyze ...

Detecting substance-related problems in narrative investigation summaries of child abuse and neglect using text mining and machine learning.

BACKGROUND: State child welfare agencies collect, store, and manage vast amounts of data. However, they often do not have the right data, or the data ...

Robotic platform for microinjection into single cells in brain tissue.

Microinjection into single cells in brain tissue is a powerful technique to study and manipulate neural stem cells. However, such microinjection requi...

Machine-learning algorithms to identify key biosecurity practices and factors associated with breeding herds reporting PRRS outbreak.

Investments in biosecurity practices are made by producers to reduce the likelihood of introducing pathogens such as porcine reproductive and respirat...

Performance of an artificial intelligence algorithm for reporting urine cytopathology.

BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite ...