ORCID Profile
0000-0002-0333-2882
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Publisher: Wiley
Date: 05-06-2023
DOI: 10.1111/JDV.19219
Abstract: Breslow thickness, patient age and ulceration are the three most valuable clinical and pathological predictors of melanoma survival. A readily available reliable online tool that accurately considers these and other predictors could be valuable for clinicians managing melanoma patients. To compare online melanoma survival prediction tools that request user input on clinical and pathological features. Search engines were used to identify available predictive nomograms. For each, clinical and pathological predictors were compared. Three tools were identified. The American Joint Committee on Cancer tool inappropriately rated thin tumours as higher risk than intermediate tumours. The University of Louisville tool was found to have six shortcomings: a requirement for sentinel node biopsy, unavailable input of thin melanoma or patients over 70 years of age and less reliable hazard ratio calculations for age, ulceration and tumour thickness. The LifeMath.net tool was found to appropriately consider tumour thickness, ulceration, age, sex, site and tumour subtype in predicting survival. The authors did not have access to the base data used to compile various prediction tools. The LifeMath.net prediction tool is the most reliable for clinicians in counselling patients with newly diagnosed primary cutaneous melanoma regarding their survival prospects.
Publisher: OMICS Publishing Group
Date: 2016
Publisher: Oxford University Press (OUP)
Date: 12-2016
DOI: 10.1111/BJD.14769
Publisher: Oxford University Press (OUP)
Date: 14-06-2017
DOI: 10.1111/BJD.15626
Publisher: Oxford University Press (OUP)
Date: 12-2022
DOI: 10.1111/BJD.21712
Publisher: Wiley
Date: 22-02-2023
DOI: 10.1111/JDV.18951
Publisher: Institution of Engineering and Technology (IET)
Date: 27-07-2023
DOI: 10.1049/HVE2.12349
Abstract: Maintenance tasks in distribution networks are often accompanied by hazards associated with high altitudes and high voltages. By utilising robots instead of human operators to perform these tasks, potential risks can be avoided, while productivity can be increased. This research proposes an intelligent power distribution live‐line operation robot (PDLOR) system based on a stereo camera to replace human to complete work. The PDLOR system consists of several key components, including dual manipulators, wireless tools, a visual perception system, an insulated bucket truck, and a ground control terminal. Once the task is confirmed, the real‐time vision system identification and positioning enable the adjustment of the insulated bucket to position the robot correctly for its intended work. The stereo camera plays a crucial role in accurately recognising and estimating the object's orientation. Additionally, a simplified reconstruction is performed within a virtual simulation environment, which aids in collision detection during path planning. After obtaining the optimal path, it is then communicated to the real manipulator for execution. To validate the feasibility of the PDLOR system, field experiments were conducted in actual distribution network scenarios. The results demonstrate that the PDLOR effectively completes single‐phase power‐line connection tasks within a remarkable 10‐min timeframe.
Location: United States of America
Location: United Kingdom of Great Britain and Northern Ireland
Location: United States of America
Location: United States of America
No related grants have been discovered for Howard Steinman.