Sikander Ailawadhi, Yaw Adu, Ryan D Frank, Saurav Das, David O Hodge, Andre Fernandez, Caitlyn Flott, Jamie Elliott, Ricardo Parrondo, Taimur Sher, Vivek Roy, Asher A Chanan-Khan
Factors determining utilization of stem cell transplant for initial therapy of multiple myeloma by patient race: exploring intra-racial healthcare disparities
Blood cancer journal
advances technology artificial intelligence smart healthcare open range possibilities precision intervention field health sciences objectives study analyse functionality using supervised prediction classification unsupervised clustering machine learning techniques analyse results related development functional skills patients developmental ages 06 years worked sample 113 patients 49 cared specific centre people motor impairments group 1 64 cared specific early care programme patients different impairments group 2 results indicated group 1 chronological age predicted development functional skills 85 group 2 65 classification variable detected functional development upper extremities two clusters detected within group allowed us determine patterns functional development patient respect functional skills use smart healthcare resources promising future field early care however data recording web applications needs planned automation results machine learning techniques required