The widespread variation in diagnosing primary headache disorders in children and adolescents results in reduced quality and high costs. Defining an algorithm for primary headache diagnoses in childre...
A team of headache specialists, nurse practitioners, nurses, data analysts, and business specialists developed an algorithm based on available scientific evidence. This algorithm was vetted and adapte...
Correct diagnosis of primary headache by International Classification of Headache Disorders-3 criteria improved from 72% to 90% and appropriate testing improved from 80% to 94%. By the end of analysis...
A standardized algorithm improved the diagnostic accuracy in general child neurology clinics. Expanding the algorithm to primary care and pediatric emergency rooms could have a greater impact on heada...
Different algorithms, such as the Savitzky-Golay filter and Whittaker smoother, have been proposed to improve the quality of experimental chromatograms. These approaches avoid excessive noise from ham...
The internal jugular vein (IJV) provides critical drainage from the brain, skull, and deep regions of the face and neck. Compromise to the bilateral IJVs has severe sequelae, but even unilateral IJV s...
We present a woman who had IJV sacrifice for an oral cavity cancer along with a contralateral selective neck dissection and adjuvant chemoradiation who developed occlusion of the contralateral IJV aft...
There were no complications from the procedure, which resulted in dissipation of her preoperative symptoms. We describe the literature surrounding IJV reconstruction, considerations for its use, the t...
IJV reconstruction is a valuable but underutilized technique for the head and neck microvascular surgeon in cases of bilateral threatened IJV outflow....
B-lines are a ring-down artifact of lung ultrasound that arise with increased alveolar water in conditions such as pulmonary edema and infectious pneumonitis. Confluent B-line presence may signify a d...
This study used a subset of 416 clips from 157 subjects, previously acquired in a prospective study enrolling adults with shortness of breath at two academic medical centers, using a hand-held tablet ...
Confluent B-lines were present in 206 of 416 clips (49.5%). Sensitivity and specificity of confluent B-line detection by algorithm compared with expert determination were 83% (95% confidence interval ...
The confluent B-line detection algorithm had high sensitivity and specificity for detection of confluent B-lines in lung ultrasound point-of-care clips, compared with expert determination....
Early breast cancer detection is associated with lower morbidity and mortality....
To examine whether a commercial artificial intelligence (AI) algorithm for breast cancer detection could estimate the development of future cancer....
This retrospective cohort study of 116 495 women aged 50 to 69 years with no prior history of breast cancer before they underwent at least 3 consecutive biennial screening examinations used scores fro...
Artificial intelligence algorithm score indicating suspicion for the presence of breast cancer. The algorithm provided a continuous cancer detection score for each examination ranging from 0 to 100, w...
Maximum AI algorithm score for cancer detection and absolute difference in score among breasts of women developing screening-detected cancer, women with interval cancer, and women who screened negativ...
The mean (SD) age at the first study round was 58.5 (4.5) years for 1265 women with screening-detected cancer in the third round, 57.4 (4.6) years for 342 women with interval cancer after 3 negative s...
In this retrospective cohort study of women undergoing screening mammography, mean absolute AI scores were higher for breasts developing vs not developing cancer 4 to 6 years before their eventual det...
Image stitching is a traditional but challenging computer vision task. The goal is to stitch together multiple images with overlapping areas into a single, natural-looking, high-resolution image witho...
Identifying individuals with depressive symptomatology (DS) promptly and effectively is of paramount importance for providing timely treatment. Machine learning models have shown promise in this area;...
This study aims to establish a novel methodology for identifying individuals likely to exhibit DS, identify the most influential features in a more explainable way via probabilistic measures, and prop...
The study used 3 data sets: PROACTIVE, the Brazilian National Health Survey (Pesquisa Nacional de Saúde [PNS]) 2013, and PNS 2019, comprising sociodemographic and health-related features. A Bayesian n...
The methodology allows the users to make an informed trade-off among sensitivity, specificity, and a reduction in the number of interviews. At the thresholds of 0.444, 0.412, and 0.472, determined by ...
This study developed a novel methodology for identifying individuals with DS, demonstrating the utility of using Bayesian networks to identify the most significant features. Moreover, this approach ha...
Time-series experiments are crucial for understanding the transient and dynamic nature of biological phenomena. These experiments, leveraging advanced classification and clustering algorithms, allow f...
The detection algorithm commonly misses obscured pedestrians in traffic scenes with a high pedestrian density because mutual occlusion among pedestrians reduces the prediction box score of the conceal...
Underwater target detection is of great significance in underwater ecological assessment and resource development. To better protect the environment and optimize the development of underwater resource...
