Machine learning and medicine: book review and commentary

This article is a review of the book “Master machine learning algorithms, discover how they work and implement them from scratch” (ISBN: not available, 37 USD, 163 pages) edited by Jason Brownlee published by the Author, edition, v1.10 http://MachineLearningMastery. com. An accompanying commentary discusses some of the issues that are involved with use of machine learning and data mining techniques to develop predictive models for diagnosis or prognosis of disease, and to call attention to additional requirements for developing diagnostic and prognostic algorithms that are generally useful in medicine. Appendix provides examples that illustrate potential problems with machine learning that are not addressed in the reviewed book

Machine learning, medical diagnosis, and biomedical engineering research - commentary

A large number of papers are appearing in the biomedical engineering literature that describe the use of machine learning techniques to develop classifiers for detection or diagnosis of disease. However, the usefulness of this approach in developing clinically validated diagnostic techniques so far has been limited and the methods are prone to overfitting and other problems which may not be immediately apparent to the investigators. This commentary is intended to help sensitize investigators as well as readers and reviewers of papers to some potential pitfalls in the development of classifiers, and suggests steps that researchers can take to help avoid these problems. Building classifiers should be viewed not simply as an add-on statistical analysis, but as part and parcel of the experimental process. Validation of classifiers for diagnostic applications should be considered as part of a much larger process of establishing the clinical validity of the diagnostic technique

TRX: A Formally Verified Parser Interpreter

Parsing is an important problem in computer science and yet surprisingly little attention has been devoted to its formal verification. In this paper, we present TRX: a parser interpreter formally developed in the proof assistant Coq, capable of producing formally correct parsers. We are using parsing expression grammars (PEGs), a formalism essentially representing recursive descent parsing, which we consider an attractive alternative to context-free grammars (CFGs). From this formalization we can extract a parser for an arbitrary PEG grammar with the warranty of total correctness, i.e., the resulting parser is terminating and correct with respect to its grammar and the semantics of PEGs; both properties formally proven in Coq.Comment: 26 pages, LMC

Classification tree to analyze factors connected with post operative complications of cataract surgery in a teaching hospital

Background: Artificial intelligence (AI) is becoming ever more frequently applied in medicine and, consequently, also in ophthalmology to improve both the quality of work for physicians and the quality of care for patients. The aim of this study is to use AI, in particular classification tree, for the evaluation of both ocular and systemic features involved in the onset of complications due to cataract surgery in a teaching hospital. Methods: The charts of 1392 eyes of 1392 patients, with a mean age of 71.3 ± 8.2 years old, were reviewed to collect the ocular and systemic data before, during and after cataract surgery, including post-operative complications. All these data were processed by a classification tree algorithm, producing more than 260 million simulations, aiming to develop a predictive model. Results: Postoperative complications were observed in 168 patients. According to the AI analysis, the pre-operative characteristics involved in the insurgence of complications were: ocular comorbidities, lower visual acuity, higher astigmatism and intra-operative complications. Conclusions: Artificial intelligence application may be an interesting tool in the physician’s hands to develop customized algorithms that can, in advance, define the post-operative complication risk. This may help in improving both the quality and the outcomes of the surgery as well as in preventing patient dissatisfaction

The even darker side of the eastern gray squirrel (Sciurus carolinensis): a review of global introductions, invasion biology, and pest management strategies

Huynh, H.M., Bertolino, S., Lurz, P.W.W., Koprowski, J.L., Williams, G.R., Thompson, C.W., McAlpine, D.F

Pore Mutations of the Escherichia coli MscS Channel Affect Desensitization but Not Ionic Preference

Mechanosensitive channels rescue bacterial cells from a fate of lysis when they transfer from a high- to low-osmolarity environment. Of three Escherichia coli mechanosensitive proteins studied to date, only MscS-Ec demonstrates a small anionic preference and a desensitized, nonconducting state under sustained pressure. Little is known about the mechanisms generating these distinctive properties. Eliminating the sole positive charge in the MscS-Ec pore region (Arg88) did not alter anionic preference. Adding positive charges at either end of the pore did not augment anionic preference, and placing negative charges within the pore did not diminish it. Thus, pore charges do not control this characteristic. However, from this analysis we identified mutations in the hinge region of the MscS-Ec pore helix (at Gly113) that profoundly affected ability of the channel to desensitize. Substitution with nonpolar (Ala, Pro) or polar (Asp, Arg, Ser) residues inhibited transition to the desensitized state. Interestingly, Gly113 replaced with Met did not impede desensitization. Thus, although Gly is not specifically required at position 113, MscS desensitization is strongly influenced by the residue situated here. Mutations at residues further into the pore also regulated desensitization. Transition to this unique mechanosensitive channel state is discussed in terms of existing data

Experimental removals reveal dietary niche partitioning facilitates coexistence between native and introduced species

Niche overlap between native species and ecologically similar invaders can lead to competitive exclusion of threatened native species, but if two such species also co-occur naturally elsewhere, interactions between native and introduced populations may mirror coevolved niche partitioning that reduces competition and promotes coexistence.A single, insular population of Fremont's squirrel (Tamiasciurus fremonti) the Mount Graham red squirrel (MGRS; T. f. grahamensis) in the Pinaleño Mountains, Arizona, USA, is critically endangered and resource competition with introduced Abert's squirrels (Sciurus aberti) may threaten its long-term persistence. The species are naturally synoptic in other mountain sites, and both consume diets comprised primarily of conifer seeds and fungi.We conducted experimental removals of introduced Abert's squirrels and used stable isotope analysis of diets before and after removals, and of diets in naturally syntopic populations to test the hypothesis that dietary niche partitioning can facilitate coexistence between native and introduced species. We also developed a novel approach to determine the influence of fluctuating food availability on carbon enrichment in consumers.Mount Graham red squirrels and introduced Abert's squirrels partitioned the dietary niche similarly to naturally syntopic populations. Removals had no apparent effect. Diet of MGRS was more closely linked to availability of resources than to presence of Abert's squirrels.Flexible dietary niche of introduced Abert's squirrels may have allowed them to exploit a resource opportunity in syntopy with MGRS. Variable food production of MGRS habitat may intensify competition in poor years, and territorial defense against non-native Abert's squirrels likely imposes fitness costs on individual MGRS. Similarity in our model species' diets may make MGRS more vulnerable to competition if climate change eliminates the advantages of larder-hoarding. Where introduced populations of ecologically similar species are better adapted to changing conditions, they may ultimately replace southern peripheral populations of native species.USDA Forest Service; American Society of Mammalogists Grant in Aid of Research; T&E Inc. Grants for Conservation Biology; University of Arizona; Arizona Game and Fish DepartmentOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Prognostic and therapeutic significance of carbohydrate antigen 19-9 as tumor marker in patients with pancreatic cancer

In pancreatic cancer ( PC) accurate determination of treatment response by imaging often remains difficult. Various efforts have been undertaken to investigate new factors which may serve as more appropriate surrogate parameters of treatment efficacy. This review focuses on the role of carbohydrate antigen 19- 9 ( CA 19- 9) as a prognostic tumor marker in PC and summarizes its contribution to monitoring treatment efficacy. We undertook a Medline/ PubMed literature search to identify relevant trials that had analyzed the prognostic impact of CA 19- 9 in patients treated with surgery, chemoradiotherapy and chemotherapy for PC. Additionally, relevant abstract publications from scientific meetings were included. In advanced PC, pretreatment CA 19- 9 levels have a prognostic impact regarding overall survival. Also a CA 19- 9 decline under chemotherapy can provide prognostic information for median survival. A 20% reduction of CA 19- 9 baseline levels within the first 8 weeks of chemotherapy appears to be sufficient to define a prognostic relevant subgroup of patients ('CA 19- 9 responder'). It still remains to be defined whether the CA 19- 9 response is a more reliable method for evaluating treatment efficacy compared to conventional imaging. Copyright (c) 2006 S. Karger AG, Basel