J. Mitsch

EFFECTIVE MODELLING OF A MAJOR INLAND OIL SPILL ON THE OHIO RIVER

J. K. Cronk, J. Mitsch, R. Sykes, 1990 .

Automated detection of lameness in sheep using machine learning approaches: novel insights into behavioural differences among lame and non-lame sheep

J. Kaler, J. Mitsch, T. Dottorini, 2020, Royal Society Open Science.

Pan-cancer analysis reveals TAp63-regulated oncogenic lncRNAs that promote cancer progression through AKT activation

K. Tsai, P. Gunaratne, K. Rajapakshe, 2020, Nature Communications.

Cluster analyses of the TCGA and a TMA dataset using the coexpression of HSP27 and CRYAB improves alignment with clinical-pathological parameters of breast cancer and suggests different epichaperome influences for each sHSP

A. Thompson, N. Mongan, P. Quinlan, 2022, Cell Stress and Chaperones.

Feature Selection and Comparison of Machine Learning Algorithms in Classification of Grazing and Rumination Behaviour in Sheep

Keith A. Ellis, Jurgen Mitsch, Jasmeet Kaler, 2018, Sensors.

Evaluation of sampling frequency, window size and sensor position for classification of sheep behaviour

Anthony Winterlich, Emily Walton, Christy Casey, 2018, Royal Society Open Science.

Police interactions and interventions with suspects flagged as experiencing mental health problems

P. Quinlan, J. Mitsch, T. Jilani, 2018, Criminal behaviour and mental health : CBMH.