Abstract: A method comprising using at least one hardware processor for: receiving a topic under consideration (TUC) and content relevant to the TUC; detecting one or more claims relevant to the TUC in the content, based on detection of boundaries of the claims in the content; and outputting a list of said detected one or more claims.

Abstract: Apparatus and methods are described for use with a cell sample. For each of one or more imaging fields of the cell sample, a depth scan of the cell sample is performed using a microscope. One of the depth levels is identified as being an optimum focal plane for imaging one or more entities within the sample using the microscope, at least partially in response to detecting that the depth level corresponds to a drop in image contrast relative to image contrast at other depth levels. Based upon the depth level identified as being the optimum focal plane for each of the one or more imaging fields of the cell sample, a scanning depth interval over which to perform a depth scan of the cell sample at a further imaging field is defined. Other applications are also described.

Abstract: The present disclosure provides a method of determining a reference depth level within a cell sample. The method comprises obtaining data representative of a series of images captured by performing a depth scan of the cell sample using a digital microscope, the series of images being associated with a series of depth levels of the cell sample; processing said data for detecting at least one depth level corresponding to a drop in image contrast; and identifying the detected depth level as the reference depth level.

Abstract: A method comprising using at least one hardware processor for: receiving a topic under consideration (TUC) and content relevant to the TUC; detecting one or more claims relevant to the TUC in the content, based on detection of boundaries of the claims in the content; and outputting a list of said detected one or more claims.

Abstract: A computer-implemented method, computerized apparatus and computer program product for claim generation, the method comprising: selecting at least one subject according to a given topic; selecting at least one verb from a first data source; selecting at least one object from a second data source; generating one or more candidate claim sentences, each of which composed of a subject selected from the at least one subject, a verb selected from the at least one verb and an object selected from the at least on object; and determining validity of the candidate claim sentences using a machine learning process.

Abstract: A method comprising using at least one hardware processor for: identifying relations between pairs of claims of a set of claims; aggregating the claims of the set of claims into a plurality of clusters based on the identified relations; generating a plurality of arguments from the plurality of clusters, wherein each of the arguments is generated from a cluster of the plurality of clusters, and wherein each of the arguments comprises at least one claim of the set of claims, scoring each possible set of a predefined number of arguments of the plurality of arguments, based on a quality of each argument of the predefined number of arguments and on diversity between the predefined number of arguments; and generating a speech, wherein the speech comprises a top scoring possible set of the possible set of the predefined number of arguments.

Abstract: The invention discloses an apparatus and method for automatic detection of pathogens within a sample. The apparatus and method are especially useful for high-throughput and/or low-cost detection of parasites with minimal need for trained personnel. The invention entails automated microscopic data acquisition, and performing image processing of images captured from a sample using classification algorithms. Visual classification features of structures are extracted from the image and compared to visual classification features associated with known pathogens. A determination is reached whether a pathogen is present in the sample; and if present, the pathogen may be identified to a pathogen species. Diagnosis is rapid and does not require medically trained personnel.

Abstract: A method comprising using at least one hardware processor for: receiving a topic under consideration (TUC) and content relevant to the TUC; detecting one or more claims relevant to the TUC in the content, based on detection of boundaries of the claims in the content; and outputting a list of said detected one or more claims.

Abstract: Apparatus and methods are described for use with a digital camera that is configured to acquire images of a bodily sample. Two or more stains are configured to stain the bodily sample. A computer processor drives the digital camera to acquire, for each of a plurality of imaging fields of the bodily sample, two or more digital images, at least one of the images being acquired under brightfield lighting conditions, and at least one of the images being acquired under fluorescent lighting conditions. The computer processor performs image processing on the digital images, by extracting visual classification features from the digital images and analyzing the extracted visual classification features. The computer processor outputs a result of the image processing that includes an indication of one or more entities that are contained within the sample. Other applications are also described.

Abstract: Methods, systems and computer program products relating to digital microscopy are disclosed. A digital microscopy method may comprise capturing a plurality of overlapping images of a sample, wherein the capturing of at least one of the plurality of images is performed while the sample and a focal plane are in relative motion along an optical axis at a speed greater than zero; and processing the plurality of images using a reference criterion to determine a reference relative arrangement of the focal plane and the sample along the optical axis.

Abstract: A method comprising using at least one hardware processor for: identifying relations between pairs of claims of a set of claims; aggregating the claims of the set of claims into a plurality of clusters based on the identified relations; generating a plurality of arguments from the plurality of clusters, wherein each of the arguments is generated from a cluster of the plurality of clusters, and wherein each of the arguments comprises at least one claim of the set of claims, scoring each possible set of a predefined number of arguments of the plurality of arguments, based on a quality of each argument of the predefined number of arguments and on diversity between the predefined number of arguments; and generating a speech, wherein the speech comprises a top scoring possible set of the possible set of the predefined number of arguments.

Abstract: Disclosed herein, inter alia, is method, kit and systems for detecting a pathogen infection in a bodily sample, the method comprising (i) staining said bodily sample with two or more dyes, comprising at least one dye predominantly staining DNA to thereby provide differential staining between DNA and at least one other cellular component being different from DNA; (ii) identifying at least a first stained area comprising the DNA, if exists in the sample, and at least one other stained area comprising the other cellular component; (iii) extracting structural features for the first stained area and the at least one other stained area, said structural features comprise at least one of (i) size of at least one of the first stained area and one other stained area and (ii) location of said first stained area and said at least one other stained area one with respect to the other; and (iv) determining the presence of a suspected pathogen in the bodily sample if a first stained area was identified and said structural fe

Abstract: The present disclosure provides a method of determining a reference depth level within a cell sample. The method comprises obtaining data representative of a series of images captured by performing a depth scan of the cell sample using a digital microscope, the series of images being associated with a series of depth levels of the cell sample; processing said data for detecting at least one depth level corresponding to a drop in image contrast; and identifying the detected depth level as the reference depth level.

Abstract: The invention discloses an apparatus and method for automatic detection of pathogens within a sample. The apparatus and method are especially useful for high-throughput and/or low-cost detection of parasites with minimal need for trained personnel. The invention entails automated microscopic data acquisition, and performing image processing of images captured from a sample using classification algorithms. Visual classification features of structures are extracted from the image and compared to visual classification features associated with known pathogens. A determination is reached whether a pathogen is present in the sample; and if present, the pathogen may be identified to a pathogen species. Diagnosis is rapid and does not require medically trained personnel.