Data Analytics as a Bridge Between Pre and Post Conditioned Osteoarthritis Handwriting: Forensic Intelligence

Data Analytics as a Bridge Between Pre and Post Conditioned Osteoarthritis Handwriting: Forensic Intelligence

연구 분야: Analysis

학회: International Conference on Artificial-Business Analytics, Quantum and Machine Learning

Data analysis prepares the forensic data of many cases that contributes the solution to the additional cases that involve forensic handwritings, signatures, ballistics, forensic chemistry and DNA analysis. Many cases have been reported where data analytics and machine learning used in crime prevention. Development of new techniques has created interventions that provided insight into examination procedure and future investigation. Data science techniques provide a unique opportunity to revolutionize forensic handwriting examination. Forensic handwriting examiners can extract, analyse, and compare handwriting features with better speed and accuracy by applying machine learning algorithms, statistical analysis, and other data-driven methodologies. Therefore, an attempt has been made to analyse the data to bridge the connection in pre and post OA conditions. In line to the previously reported cases, the present research has been conducted to study the impact of osteoarthritis (OA) handwriting features in comparison pre-and post-conditioned samples using statistical analysis. Osteoarthritis (OA) is a joint disorder that can cause discomfort, stiffness, and pain. As the illness can affect any joint in the body; hips, knees, and hands are the most commonly affected body parts. In present research study, pre- and post-conditioned OA handwriting features are statistically analysed as well as qualitatively analysed. Data science has aided in identification of deviation in handwriting characteristics from pre to post conditioned OA handwriting features. This can give forensic handwriting examiners important insights and help them draw more accurate and dependable conclusions.