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Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.

Human brain mapping
This study investigated whether current state-of-the-art deep reasoning network analysis on psychometry-driven diffusion tractography connectome can accurately predict expressive and receptive language scores in a cohort of young children with persis...

AI-based pathology predicts origins for cancers of unknown primary.

Nature
Cancer of unknown primary (CUP) origin is an enigmatic group of diagnoses in which the primary anatomical site of tumour origin cannot be determined. This poses a considerable challenge, as modern therapeutics are predominantly specific to the primar...

The persuasive power of robot touch. Behavioral and evaluative consequences of non-functional touch from a robot.

PloS one
The unique physical embodiment of robots enables physical contact between machines and humans. Since interpersonal touch research has demonstrated that touch has several positive behavioral (e.g., reduced stress, better immune functioning) as well as...

Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study.

European radiology
OBJECTIVES: Digital breast tomosynthesis (DBT) increases sensitivity of mammography and is increasingly implemented in breast cancer screening. However, the large volume of images increases the risk of reading errors and reading time. This study aims...

A machine learning approach to screen for preclinical Alzheimer's disease.

Neurobiology of aging
Combining multimodal biomarkers could help in the early diagnosis of Alzheimer's disease (AD). We included 304 cognitively normal individuals from the INSIGHT-preAD cohort. Amyloid and neurodegeneration were assessed on F-florbetapir and F-fluorodeox...

Deep Learning-Based Artificial Intelligence for Mammography.

Korean journal of radiology
During the past decade, researchers have investigated the use of computer-aided mammography interpretation. With the application of deep learning technology, artificial intelligence (AI)-based algorithms for mammography have shown promising results i...

Deep Learning for Fully Automated Prediction of Overall Survival in Patients with Oropharyngeal Cancer Using FDG-PET Imaging.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Accurate prognostic stratification of patients with oropharyngeal squamous cell carcinoma (OPSCC) is crucial. We developed an objective and robust deep learning-based fully-automated tool called the DeepPET-OPSCC biomarker for predicting ove...

Cesarean scar pregnancy: Reproductive outcome after robotic laparoscopic removal with simultaneous repair of the uterine defect.

European journal of obstetrics, gynecology, and reproductive biology
OBJECTIVE: To describe perioperative adverse events, fertility and obstetric outcome, following a robot assisted laparoscopic approach for treating Cesarean scar pregnancies (CSP).

AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation.

Radiology
Background The workflow of breast cancer screening programs could be improved given the high workload and the high number of false-positive and false-negative assessments. Purpose To evaluate if using an artificial intelligence (AI) system could redu...