Stephen William Hawking CH CBE FRS FRSA (8 January 1942 – 14 March 2018) was an English theoretical physicist, cosmologist, author and Director of Research at the Centre for Theoretical Cosmology within the University of Cambridge. His scientific works included a collaboration with Roger Penrose on gravitational singularity theorems in the framework of general relativity and the theoretical prediction that black holes emit radiation, often called Hawking radiation. Hawking was the first to set out a theory of cosmology explained by a union of the general theory of relativity and quantum mechanics. He was a vigorous supporter of the many-worlds interpretation of quantum mechanics. Hawking was an Honorary Fellow of the Royal Society of Arts (FRSA), a lifetime member of the Pontifical Academy of Sciences, and a recipient of the Presidential Medal of Freedom, the highest civilian award in the United States. In 2002, Hawking was ranked number 25 in the BBC's poll of the 100 Greatest Britons. He was the Lucasian Professor of Mathematics at the University of Cambridge between 1979 and 2009 and achieved commercial success with works of popular science in which he discusses his own theories and cosmology in general. His book, A Brief History of Time, appeared on the British Sunday Times best-seller list for a record-breaking 237 weeks. Hawking had a rare early-onset slow-progressing form of motor neurone disease (also known as amyotrophic lateral sclerosis and Lou Gehrig's disease), that gradually paralysed him over the decades. Even after the loss of his speech, he was still able to communicate through a speech-generating device, initially through use of a hand-held switch, and eventually by using a single cheek muscle. Hawking was born on 8 January 1942 in Oxford to Frank (1905–1986) and Isobel Hawking (née Walker; 1915–2013). Despite their families' financial constraints, both parents attended the University of Oxford, where Frank read medicine and Isobel read Philosophy, Politics and Economics. The two met shortly after the beginning of the Second World War at a medical research institute where Isobel was working as a secretary and Frank was working as a medical researcher. They lived in Highgate; but, as London was being bombed in those years, Isobel went to Oxford to give birth in greater safety. Hawking had two younger sisters, Philippa and Mary, and an adopted brother, Edward. In 1950, when Hawking's father became head of the division of parasitology at the National Institute for Medical Research, Hawking and his family moved to St Albans, Hertfordshire.
The University of Cambridge professor was an iconic figure in both the scientific community and in popular culture, known for his keen mind and humor, as well as his striking physical challenges. Dr. Hawking had long battled with amyotrophic lateral sclerosis, which left him wheelchair-bound for most of his life. Commonly known as Lou Gehrig's disease or motor neuron disease, the condition damages the nerves that control movement and results in paralysis. Patients with ALS typically die within five years of diagnosis. Dr. Hawking, who was diagnosed in 1963 at the age of 21, is believed to have been the longest-living survivor, a fact that still perplexes neurologists.
Data-driven techniques for identifying disease subtypes using medical records can greatly benefit the management of patients' health and unravel the underpinnings of diseases. Clinical patient records are typically collected from disparate sources and result in high-dimensional data comprising of multiple likelihoods with noisy and missing values. Probabilistic methods capable of analysing large-scale patient records have a central role in biomedical research and are expected to become even more important when data-driven personalised medicine will be established in clinical practise. In this work we propose an unsupervised, generative model that can identify clustering among patients in a latent space while making use of all available data (i.e. in a heterogeneous data setting with noisy and missing values). We make use of the Gaussian process latent variable models (GPLVM) and deep neural networks to create a non-linear dimensionality reduction technique for heterogeneous data. The effectiveness of our model is demonstrated on clinical data of Parkinson's disease patients treated at the HUS Helsinki University Hospital. We demonstrate sub-groups from the heterogeneous patient data, evaluate the robustness of the findings, and interpret cluster characteristics.
After revolutionizing various industry sectors, the introduction of artificial intelligence in healthcare is transforming how we diagnose and treat critical disorders. A team of experts in the Laboratory for Respiratory Diseases at the Catholic University of Leuven, Belgium, trained an AI-based computer algorithm using good quality data. Dr. Marko Topalovic, a postdoctoral researcher in the team, announced that AI was found to be more consistent and accurate in interpreting respiratory test results and in suggesting diagnoses, as compared to lung specialists. Likewise, Artificial Intelligence Research Centre for Neurological Disorders at the Beijing Tiantan Hospital and a research team from the Capital Medical University developed the BioMind AI system, which correctly diagnosed brain tumor in 87% of 225 cases in about 15 minutes, whereas the results of a team of 15 senior doctors displayed only 66% accuracy. The introduction of technologies such as deep learning and artificial intelligence in healthcare can help achieve more efficiency and precision.
Janssen Research & Development seeks to drive innovation and deliver transformational medicines for the treatment of diseases in six therapeutic areas: neuroscience, cardiovascular diseases and metabolism, infectious diseases, immunology, oncology and pulmonary hypertension. In these areas, Janssen aims to address and solve unmet medical needs through the development of small and large molecules, as well as vaccines. The Janssen campus in Beerse (Belgium) has a unique ecosystem covering the complete drug development life cycle, with all capabilities from basic science to market access on one campus. The integrated environment of our campus gives our people the chance to experience many different aspects of drug development throughout their career. It has a successful track record of over sixty years of drug discovery and development and is one of the most important innovation engines of the Janssen group worldwide.