A unique aspect of our approach is its ability to offer, along with each positive prediction, explanations in the form of subgraphs, revealing the specific entities and relationships that led to each pathogenic prediction. Conclusion Our method, built with interpretability in mind, leverages ...
This is determined by the threshold, usually 5%, to decide whether a point is an outlier in our dataset. This will also help us in terms of generalization and robustness on unseen data, since any future data points that form new clusters with very few members are considered outliers. Our ...
A complete blood count (CBC) can be used to determine a person’s high-risk status for a particular form of cancer. This is justified because many cancer patients will inevitably have particular CBC patterns. Abnormalities in blood haemoglobin (HGB) levels, neutropenia, severe anaemia, or ...
Focus on building strong concepts, especially in Quantitative Aptitude, Reasoning Ability, and English Language, as these form the core sections of most bank exams. Daily practice is key solve at least 4-5 puzzles, Data Interpretation (DI) sets, and reading editorials to strengthen your reasoning...
So-called NHA (Normal Human Astrocytes) cells belong to the class of GFAP-positive neural progenitors. Expression of neuronal and glial markers during differentiation of these cells is regulated in accordance with the "model of discordant phenotypes suppression" [1–3]. This model states that befor...
of the settings delineated in the previous section (the baselines, raw aggregative, weighted aggregative and integrative settings); we also ran the calculations using several different groupwise single-ontology measures (Resnik +BMA [35, 36], Lin +BMA [36, 37], simUI [38] and simGIC [36])...
(DL) systems with a large number of parameters, leading to remarkable achievements in domains such as computer vision, machine translation, game playing, and others. One key feature of deep learning systems is their ability to more effectively capture data and workload distributions compared to ...
we aimed to evaluate the quality of the learned vectors by computing the functional similarity between proteins on the CESSM dataset [31]. We compare the results with the representative information content based methods, namely Resnik [7], Lin [6], Jang&Conrath [5], simGIC [33], and simUI...
Big data is a term used for very large data sets that have more varied and complex structure. These characteristics usually correlate with additional difficulties in storing, analyzing and applying further procedures or extracting results. Big data analy
Perversely, sexual appropriation in this feminism still has the epistemolo-gical status of labour; that is to say, the point from which an analysis able to contribute to changing the world must flow. But sexual object)fication, not alienation, is the consequence of the structure of sex/gender...