most citedEvaluating Performance of Machine Learning Models for Diabetic Sensorimotor Polyneuropathy Severity Classification using Biomechanical Signals during Gait

4 citations · 6 across the 4 of their papers we have counts for

collaborators

4 papers

cs.CV2022★ 1 cited

Deep Learning based Automatic Quantification of Urethral Plate Quality using the Plate Objective Scoring Tool (POST)

Tariq O. Abbas, Mohamed AbdelMoniem, Ibrahim Khalil +2

Objectives: To explore the capacity of deep learning algorithm to further streamline and optimize urethral plate (UP) quality appraisal on 2D images using the plate objective scori…

physics.med-ph2022

Design and Implementation of a Complete Wearable Smart Insole Solution to Measure Plantar Pressure and Temperature

Amith Khandakar, Sakib Mahmud, Muhammad E. H. Chowdhury +7

A complete smart insole solution that continuously monitors the foot plantar pressure and temperature can detect foot complications early and that too from the convenience of the u…

cs.LG2022★ 4 cited

Evaluating Performance of Machine Learning Models for Diabetic Sensorimotor Polyneuropathy Severity Classification using Biomechanical Signals during Gait

Fahmida Haque, Mamun Bin Ibne Reaz, Muhammad Enamul Hoque Chowdhury +10

Diabetic sensorimotor polyneuropathy (DSPN) is one of the prevalent forms of neuropathy affected by diabetic patients that involves alterations in biomechanical changes in human ga…

cs.LG2022★ 1 cited

A machine learning-based severity prediction tool for diabetic sensorimotor polyneuropathy using Michigan neuropathy screening instrumentations

Fahmida Haque, Mamun B. I. Reaz, Muhammad E. H. Chowdhury +7

Background: Diabetic Sensorimotor polyneuropathy (DSPN) is a major long-term complication in diabetic patients associated with painful neuropathy, foot ulceration and amputation. T…