Design and Development of an Autonomous Car using Object Detection with YOLOv4

Future cars are anticipated to be driverless point-to-point transportation services capable of avoiding fatalities To achieve this goal auto-manufacturers have been investing to realize the potential autonomous driving In this regard we present a self-driving model car capable of autonomous driving using object-detection as a primary means of steering on a track made of colored cones This paper goes through the process of fabricating a model vehicle from its embedded hardware platform to the end-to-end ML pipeline necessary for automated data acquisition and model-training thereby allowing a Deep Learning model to derive input from the hardware platform to control the car s movements This guides the car autonomously and adapts well to real-time tracks without manual feature-extraction This paper presents a Computer Vision model that learns from video data and involves Image Processing Augmentation Behavioral Cloning and a Convolutional Neural Network model The Darknet architecture is used to detect objects through a video segment and convert it into a 3D navigable path Finally the paper touches upon the conclusion results and scope of future improvement in the technique use

The effect of age in the outcome and treatment of older women with ductal carcinoma in situ

AbstractThe effect of increasing age on outcomes and type of treatment given to older women with ductal carcinoma in situ (DCIS) was assessed. 646 women ≥60 years old (654 cases) receiving surgery for DCIS at Memorial Sloan-Kettering Cancer Center between 2000 and 2007 (8 bilateral) had wide local excision (WLE; 37%), WLE plus radiotherapy (WLE+RT; 41%), or mastectomy (22%). 45%, 38%, and 16% of patients 60–69 years, 70–79 years, and ≥80 years, respectively, received WLE+RT (P<0.001) and 25%, 20%, and 13%, received mastectomy, respectively (P<0.001). Age (P<0.001), grade (P<0.001), and necrosis (P<0.01) were highly associated with treatment. Four-year local recurrence was 3.6%. Overall local recurrence differed by treatment (mastectomy, 0%; WLE, 5%; WLE+RT, 4%; P<0.00001) but not age. It is possible to identify older women with DCIS in whom the risk of recurrence is acceptably low after WLE alone. WLE alone may be a viable treatment option for select older women with DCIS

Transcriptional diversity of long-term glioblastoma survivors

BACKGROUND: Glioblastoma (GBM) is a highly aggressive type of glioma with poor prognosis. However, a small number of patients live much longer than the median survival. A better understanding of these long-term survivors (LTSs) may provide important insight into the biology of GBM. METHODS: We identified 7 patients with GBM, treated at Memorial Sloan-Kettering Cancer Center (MSKCC), with survival \u3e48 months. We characterized the transcriptome of each patient and determined rates of MGMT promoter methylation and IDH1 and IDH2 mutational status. We identified LTSs in 2 independent cohorts (The Cancer Genome Atlas [TCGA] and NCI Repository for Molecular Brain Neoplasia Data [REMBRANDT]) and analyzed the transcriptomal characteristics of these LTSs. RESULTS: The median overall survival of our cohort was 62.5 months. LTSs were distributed between the proneural (n = 2), neural (n = 2), classical (n = 2), and mesenchymal (n = 1) subtypes. Similarly, LTS in the TCGA and REMBRANDT cohorts demonstrated diverse transcriptomal subclassification identities. The majority of the MSKCC LTSs (71%) were found to have methylation of the MGMT promoter. None of the patients had an IDH1 or IDH2 mutation, and IDH mutation occurred in a minority of the TCGA LTSs as well. A set of 60 genes was found to be differentially expressed in the MSKCC and TCGA LTSs. CONCLUSIONS: While IDH mutant proneural tumors impart a better prognosis in the short-term, survival beyond 4 years does not require IDH mutation and is not dictated by a single transcriptional subclass. In contrast, MGMT methylation continues to have strong prognostic value for survival beyond 4 years. These findings have substantial impact for understanding GBM biology and progression